Fact-checked by Grok 2 weeks ago

Flicker noise

Flicker noise, also known as 1/f noise, is a fundamental type of low-frequency electronic observed in a wide range of physical systems, characterized by a power that varies inversely with , typically following the form S(f) \propto 1/f^\alpha where \alpha is approximately 1 (ranging from 0.5 to 1.5). This exhibits scale-invariant , often spanning several decades of , and is distinct from (which is frequency-independent) or due to its increasing power at lower frequencies. It manifests in semiconductors, resistors, vacuum tubes, and even natural phenomena like earthquakes or biological signals, making it a ubiquitous challenge in precision and . The phenomenon was first systematically observed in 1925 by J. B. Johnson in vacuum tubes, where it was attributed to fluctuations in electron emission from cathode sites due to trapping and release mechanisms. Subsequent explanations, such as those by W. Schottky in the 1930s, linked it to distributed relaxation times in material defects, while later models in the 1970s connected it to fractal structures and self-organized criticality. In semiconductors, flicker noise primarily arises from carrier trapping and detrapping at interfaces (e.g., silicon-oxide boundaries) or mobility fluctuations within the material, leading to variations in conductance. In electronic devices like MOSFETs and CMOS transistors, flicker noise dominates below approximately 1 kHz and is modeled using approaches such as the McWhorter number fluctuation theory, which attributes it to random charge capture/emission by oxide traps, or Hooge's empirical relation, which correlates noise amplitude with total carrier number and device geometry. Its magnitude is often quantified by the flicker noise coefficient K_f or Hooge parameter \alpha_H \approx 10^{-3} to $10^{-6}, depending on material quality and fabrication processes. This noise degrades signal-to-noise ratios in analog circuits, oscillators, and sensors, prompting mitigation strategies like chopper stabilization or careful bias design in modern integrated circuits. Despite extensive study, the precise microscopic origins remain debated, with ongoing research exploring its implications in nanoscale devices and quantum technologies.

Fundamentals

Definition and Terminology

Flicker noise is a type of low-frequency characterized by a power that varies inversely with , expressed as S(f) \propto 1/f. This form of is prevalent in devices and systems, where it dominates at lower frequencies compared to other types. It is commonly referred to as 1/f due to its defining spectral dependence, and in broader contexts, as because its power distribution per octave resembles the equal-energy spectrum of pink light in the visible range. The term "flicker " specifically arose from early observations of irregular, light-like fluctuations in the plate of vacuum tubes, evoking the visual effect of flickering. In standardized IEEE , "flicker " is the preferred formal designation, distinguishing it from the more descriptive but informal "1/f ." Unlike white noise, which exhibits a flat power spectral density across frequencies, flicker noise increases in intensity as frequency decreases, making it particularly prominent in low-frequency applications. In contrast, brown noise features a steeper $1/f^2 dependence, concentrating even more power at lower frequencies. Thermal noise and shot noise, by comparison, represent constant power spectral density alternatives typical of white noise sources in electronic circuits.

Historical Background

Flicker noise, also known as 1/f noise due to its characteristic power inversely proportional to frequency, was first observed in the during studies of amplifiers. In 1925, J.B. Johnson at Bell Laboratories reported low-frequency fluctuations in the emission current of oxide-coated and filaments, which he termed the "flicker effect," initially attributing it to variations in electron emission rates rather than distinguishing it clearly from . By 1926, Walter Schottky analyzed these observations theoretically, linking the flicker effect to irregular surface processes and space-charge smoothing, though early interpretations often conflated it with other thermal and mechanisms in tubes and early resistors. Through the 1930s and 1940s, similar excess low-frequency was noted in carbon resistors and early devices, but it remained empirically described without a unified framework, frequently misattributed to contact potentials or impurity effects. The marked the formal recognition of flicker as a distinct 1/f phenomenon in semiconductors, shifting focus from vacuum tubes to solid-state devices. In 1969, Frank N. Hooge introduced an empirical model for 1/f in homogeneous materials, proposing the Hooge parameter α_H to quantify the relative noise magnitude as S_V / V^2 = α_H / (N f), where N is the total number of carriers, establishing a scalable relation independent of specific defect mechanisms. This parameter-based approach facilitated quantitative predictions and became a cornerstone for noise characterization in resistors and early transistors, emphasizing its bulk origin over surface effects. Advancements in the broadened the understanding of flicker noise beyond , revealing its ubiquity across physical systems. In 1976, Richard F. Voss and John Clarke demonstrated that 1/f voltage noise in continuous metal films at arises from temperature fluctuations, with power spectra scaling as 1/f over several decades, extending the phenomenon to processes. Concurrently, their 1978 work showed 1/f spectra in audio power fluctuations of music and speech, suggesting self-similar scaling in natural signals. In 1978, H.G.E. Beck and W.P. Spruit provided a quantum mechanical interpretation, modeling 1/f noise in the variance of thermal noise through superposition of spectra from distributed relaxation times, linking it to quantum tunneling of charge carriers. From the 1980s to the 2000s, flicker noise was increasingly integrated into device physics models, particularly for MOSFETs, where it limited low-frequency performance in analog circuits. Early models invoked carrier number fluctuations via trapped charges at the oxide interface (McWhorter model, originally 1957 but refined in the ), while correlated mobility fluctuations gained prominence. A key milestone was the 1990 unified model by Hung et al., combining number and mobility fluctuation mechanisms to fit experimental data across operating regions, enabling accurate simulations for VLSI design. This era saw empirical Hooge parameters applied to scaling laws in shrinking transistors, with noise levels rising inversely with gate area. Post-2020 research has reignited debates on flicker noise's fundamental origins, particularly in quantum technologies, emphasizing non-Gaussian statistics and quantum mechanisms over classical interpretations. Studies on superconducting qubits reveal 1/f flux noise evolving with applied magnetic fields, suggesting origins in surface spin clusters that impact decoherence. Quantum models, building on Handel's mobility fluctuation theory, propose 1/f spectra from photon-assisted processes, with recent analyses questioning Gaussian validity in non-equilibrium systems like torque oscillators. These investigations highlight ongoing shifts from empirical to theoretically grounded models, with implications for noise mitigation in . Recent studies (as of 2024) continue to explore noise mitigation in quantum devices through material improvements and field-dependent analyses.
YearMilestoneKey Contribution
1925Johnson's observationFirst report of flicker effect in vacuum tube currents, linked to cathode emission irregularities.
1926Schottky's analysisTheoretical distinction of flicker from shot noise, attributing it to surface processes.
1969Hooge parameterEmpirical formula for 1/f noise in semiconductors, α_H / (N f).
1976Voss-Clarke equilibrium noise1/f resistance fluctuations from temperature variations in metals.
1978Beck-Spruit quantum modelSuperposition of Lorentzians explaining 1/f in Johnson noise variance.
1990Unified MOSFET modelIntegration of number and mobility fluctuations for circuit simulation.
2023Qubit flux noise evolution with magnetic fieldsSurface spin cluster origins in quantum devices.

Physical Origins

Causes in Electronic Devices

In semiconductors such as MOSFETs, flicker noise primarily arises from two dominant mechanisms: carrier number fluctuations due to trapping and detrapping of charge carriers at the oxide-semiconductor , as described by the McWhorter model, and mobility fluctuations caused by from charged impurities or defects in the channel. The number fluctuation mechanism involves random capture and emission of carriers by traps, leading to variations in the effective carrier density, while mobility fluctuations result from perturbations in the rate that affect carrier transport. These processes are exacerbated by contaminants and manufacturing defects, such as impurities or lattice imperfections, which introduce additional trapping sites and amplify the noise level. The overall magnitude of flicker noise in these devices is often empirically characterized by Hooge's relation, which states that the relative noise power spectral density is proportional to α_H / (f N), where α_H is the Hooge parameter (typically 10^{-3} to 10^{-6}), f is frequency, and N is the total number of free carriers. In resistors, flicker noise stems from local temperature fluctuations that cause resistance variations through the temperature coefficient of resistance, though this effect is negligible in stable alloys like manganin due to their low temperature coefficient. Carbon-composition resistors exhibit particularly high levels of this excess noise owing to their granular structure, which promotes irregular current paths and enhanced scattering. In diodes and bipolar junction transistors (BJTs), flicker noise is generated by non-linear effects associated with bias , including recombination-generation processes at defects and that lead to fluctuations. These bias-dependent contributions dominate at low frequencies and increase with . For example, JFETs and BJTs typically show a flicker noise corner frequency around 1 kHz, where flicker noise equals , whereas in MOSFETs this corner can extend to 10 MHz or higher due to improved interface quality in modern fabrication.

Mechanisms in Non-Electronic Systems

Flicker noise, characterized by its 1/f , manifests in various non-electronic systems, revealing universal behaviors across natural phenomena. Pioneering experiments by and Clarke in 1976 demonstrated the presence of 1/f noise in equilibrium , such as temperature variations in resistors and fluids, confirming that such noise arises even without external driving forces. Their subsequent work extended these findings to biological signals, including and fluctuations in music and speech, where power spectra exhibited 1/f scaling over multiple octaves, suggesting intrinsic correlations in human-generated acoustic patterns. Similar 1/f characteristics have been observed in , where interbeat intervals display long-range correlations indicative of healthy physiological regulation. Physical mechanisms underlying flicker noise in these systems often involve diffusion-limited processes, where random walks or particle migrations in disordered environments generate low-frequency fluctuations. For instance, in porous media or fluids, the superposition of diffusive motions with varying timescales yields a 1/f spectrum due to the broad distribution of relaxation times. Another key mechanism is , as proposed by Bak, Tang, and Wiesenfeld in 1987, where systems like sandpile models evolve to a critical through dynamics, producing power-law distributed events that result in 1/f noise. In disordered media, such as amorphous materials or turbulent flows, avalanche-like relaxations of trapped charges or eddies contribute to this noise via collective, scale-invariant responses. More recently, in 2024, delta-T flicker noise was demonstrated in molecular junctions under temperature gradients, highlighting temperature-difference induced resistance fluctuations as a mechanism in nanoscale systems. Representative examples abound in diverse domains. In optical systems, phase noise often follows 1/f scaling, arising from thermal and mechanical fluctuations in the cavity that couple to frequency drifts over long timescales. Acoustic signals from natural , such as wind gusts or river flows, exhibit 1/f in velocity and pressure spectra, reflecting the hierarchical energy cascade in turbulent eddies. In , flux in superconducting quantum interference devices (SQUIDs) displays prominent 1/f behavior, attributed to atomic-scale defects or spin fluctuations that induce variations. Universal scaling theories link these phenomena to and structures, where self-similar patterns across scales—evident in the branching of or the geometry of turbulent flows—underpin the 1/f distribution. Recent findings in the highlight flicker noise as an emergent property in complex datasets; for example, analyses of climate records reveal 1/f-like spectra in temperature and precipitation variability, signaling long-memory dynamics in Earth's systems. Similarly, neural signals from brain activity show 1/f scaling in , driven by noise-sustained oscillations that maintain network stability. These observations underscore flicker noise as a hallmark of self-organizing, far-from-equilibrium processes in .

Mathematical Modeling

Power Spectral Density

Flicker noise is characterized by its power (PSD), which empirically follows the form S(f) = \frac{h}{f^\beta}, where f is the in Hz, h is a system-dependent noise intensity coefficient that determines the overall level, and \beta is the exponent typically approximating 1 for standard flicker noise. This functional dependence was first observed through experimental measurements in early electronic devices, such as vacuum tubes, where the was found to decrease inversely with over multiple decades. The corner f_c, also known as the 1/f corner, marks the point in the where the flicker PSD equals the level of , such as , below which flicker dominates. For instance, in metal-oxide-semiconductor field-effect transistors (MOSFETs), this is commonly given by f_c = \frac{K_F g_m}{4 k_B T \gamma C_{\rm ox} W L}, where K_F is the flicker related to and , g_m is the , k_B is Boltzmann's , T is the , \gamma \approx 2/3 in , C_{\rm ox} is the oxide per unit area, and W, L are the width and length; this expression arises from equating the flicker current to the contributions. In a log-log plot of PSD versus frequency, the signature of flicker noise is a straight line with a slope of -\beta, approximately -1, spanning several orders of magnitude in frequency and distinguishing it from flat white noise spectra at higher frequencies. The PSD units are conventionally V²/Hz for voltage fluctuations or A²/Hz for current fluctuations, reflecting power per unit bandwidth; the total noise power is then computed by integrating S(f) over the bandwidth of interest, yielding a value proportional to h \ln(f_2 / f_1) for \beta = 1 between lower limit f_1 and upper limit f_2. While the ideal form assumes \beta = 1, real systems exhibit deviations where \beta ranges from 0.8 to 1.2, influenced by factors such as defects, , or setup, leading to slight or altered slopes in the low-frequency regime.

Device-Specific Formulations

In metal-oxide-semiconductor field-effect transistors (MOSFETs), flicker noise is commonly modeled using the carrier number fluctuation theory, where the input-referred gate voltage spectral density is given by S_v = \frac{K_f}{C_{\rm ox} W L f}, with K_f being a process-dependent parameter typically ranging from $10^{-28} to $10^{-24} C²/cm², C_{\rm ox} the gate oxide capacitance per unit area, W and L the channel width and length, and f the frequency. This formulation stems from the McWhorter model, attributing noise to random trapping and detrapping of carriers at the oxide-semiconductor interface. An extension to the drain current noise power spectral density incorporates mobility fluctuations, expressed as S_{i_d} = \frac{K_i I_d^\gamma}{W L f}, where K_i is another process parameter, I_d the , and \gamma \approx 2 reflecting quadratic dependence on in many processes. This semi-empirical form captures observed non-linear behavior in saturation and linear regions. For resistors, the total voltage noise includes both thermal and flicker components: e_n^2 = 4 k T R \Delta f + \frac{\alpha_H V^2 \Delta f}{N f}, where k is Boltzmann's constant, T temperature, R resistance, \Delta f bandwidth, V applied voltage, N the total number of charge carriers, and \alpha_H the Hooge parameter. The flicker term arises empirically from mobility or number fluctuations in the conducting volume. In bipolar junction transistors (BJTs) and diodes, flicker noise exhibits non-linear current dependence, with the current noise spectral density for the collector current in BJTs modeled as S_i \propto I_c / f, attributed to recombination processes in the base region. Similar recombination mechanisms dominate in diodes, leading to comparable 1/f scaling with forward bias current. The Hooge parameter \alpha_H, typically ranging from $10^{-6} to $10^{-3}, provides a scaling factor for empirical predictions across these devices, linking to density. These models remain semi-empirical, relying on fitted parameters; recent analyses post-2020 highlight their oversimplification in nanoscale devices, where quantum effects and interface variations introduce deviations from classical assumptions.

Properties

Frequency and Amplitude Characteristics

Flicker noise exhibits a characteristic frequency dependence where its power spectral density is inversely proportional to , typically dominating from (DC) up to approximately 10 kHz in many electronic devices, beyond which it diminishes relative to components. The precise range varies by device type and operating conditions; for instance, in audio amplifiers, the corner —where flicker noise equals thermal noise—often lies around 1 Hz to 100 Hz, allowing it to significantly influence low-frequency audio signals. In (RF) applications, such as mixers and oscillators, this corner can extend to 100 kHz or even 1 MHz, affecting and at higher operating bands. Overall, the noise persists over several decades of , sometimes spanning more than six orders from $10^{-6} Hz upward in operational amplifiers and resistors, with the exponent \alpha in $1/f^\alpha typically ranging from 0.5 to 1.5. The amplitude of flicker noise increases markedly at lower frequencies, often becoming the dominant source below the corner frequency f_c, where it can exceed thermal by orders of magnitude. In resistors, this manifests as excess , particularly in carbon-composition or thick-film types due to granular structure fluctuations, and at low frequencies can be significantly above the thermal . For active devices like transistors, the scales with the square of the bias , amplifying in high- regimes. To quantify the impact, the total root-mean-square () over a can be estimated by integrating the power S(f) across the band of interest; for example, in a low-pass filtered from 0.1 Hz to 10 Hz with a 1/f corner at 60 Hz and density of 55 nV/√Hz at 1 Hz, the flicker contribution yields approximately 139 nV , dominating the broadband thermal of 476 nV in that range. Flicker noise behaves linearly in passive networks, adding in for parallel components, similar to other uncorrelated noise sources, which simplifies noise budgeting in . Its temperature dependence is generally weaker than that of thermal noise, showing only slight variations in mobility fluctuation models from 250 K to 300 K in MOSFETs, though defect-related mechanisms can amplify it at elevated temperatures by increasing activity. In power spectra, flicker noise appears as a sloping "1/f tail" that rises toward lower frequencies, contrasting sharply with the flat profile of ; this visual distinction is evident in plots of voltage noise density versus log frequency, where the flicker regime creates a -10 /decade slope up to the corner, beyond which the spectrum levels off. Such characteristics underscore its role in limiting precision at low frequencies across diverse applications.

Statistical Behavior

Flicker noise is conventionally modeled as having a for its amplitude fluctuations, consistent with the applied to aggregated microscopic processes in many electronic systems. However, this assumption has faced challenges from recent investigations, particularly in 2023 studies of devices, which reveal non-Gaussian tails in the distribution attributed to intermittent such as the heterogeneous detrapping of individual charge carriers. These tails arise because rare, large-amplitude bursts from single-carrier dynamics contribute disproportionately to the noise statistics, deviating from the symmetric, bell-shaped Gaussian form expected under additive, independent contributions. In the , flicker noise demonstrates pronounced long-term correlations that produce "" effects, where fluctuations at one instant influence those far into the future, in stark contrast to the instantaneous independence of . The function exhibits a slow power-law , reflecting the persistent temporal inherent to the noise process. These correlations stem from underlying mechanisms like and release in materials, leading to a non-Markovian that sustains dependencies over extended timescales. Flicker noise is approximately over short observation periods, meaning its statistical properties remain consistent within those windows, but it often displays non-stationary drifts in DC-biased systems due to evolving bias-dependent states. This limited stationarity complicates long-term analysis. Furthermore, flicker noise violates strict , resulting in discrepancies between ensemble averages (across multiple realizations) and time averages (from a single ), particularly evident in low-frequency regimes where finite observation times fail to sample the full variability. These statistical traits have key implications for : the long-term correlations and breakdown cause the variance of integrated signals to remain elevated over prolonged periods, unlike where variance diminishes with integration time, thereby limiting the benefits of averaging in flicker-dominated environments.

Measurement Techniques

Instrumentation Methods

Flicker noise, characterized by its 1/f power , requires specialized instrumentation to capture signals at low frequencies where signal-to-noise ratios (SNR) are often poor. FFT-based spectrum analyzers are commonly employed for broadband measurements extending down to millihertz (mHz) ranges, enabling simultaneous acquisition across multiple frequency bins without the sequential scanning limitations of swept analyzers. Unlike swept analyzers, which can introduce artifacts in low-SNR environments due to their narrower instantaneous , FFT methods provide superior and information, making them ideal for flicker noise characterization in devices like transistors. Test setups for flicker noise measurement typically incorporate bias networks to maintain stable operating conditions for the device under test (DUT), such as transistors biased with constant current sources to avoid modulation of noise by voltage fluctuations. Shielding enclosures, often using μ-metal or Faraday cages, are essential to minimize external electromagnetic interference, while probe configurations—such as differential voltage or current sensing with low-impedance tungsten tips—ensure accurate capture of noise without introducing additional artifacts. For high-impedance DUTs, JFET-based preamplifiers are preferred over BJT types to reduce equivalent input current noise. Specialized tools enhance measurement precision in challenging scenarios. Cross-correlation techniques, implemented via dual-channel amplifiers and synchronous analog-to-digital converters, reject uncorrelated amplifier noise, allowing on-chip flicker noise detection with sensitivities below 100 pV/√Hz at 1 Hz. Lock-in amplifiers provide sub-Hz frequency resolution by phase-sensitive detection, effectively isolating flicker components through narrowband filtering and low-pass integration, achieving noise floors as low as a few nanovolts in mHz regimes. Calibration of these systems relies on reference noise sources, such as known resistors (e.g., 10 Ω units), to validate , , and overall , ensuring measurements align with Johnson-Nyquist predictions before DUT testing.

Data Analysis Approaches

Analysis of flicker noise data begins with estimating the power (PSD) from time-domain measurements of voltage or current fluctuations. The method provides a basic PSD estimate but suffers from high variance, particularly at low frequencies where flicker noise dominates. To mitigate this, segments the data into overlapping windows, applies windowing (e.g., Hanning), computes the for each, and averages the results, reducing variance while preserving resolution. This approach is widely used for flicker noise characterization, as it effectively handles the 1/f^β spectrum with β ≈ 1. Once the is obtained, it is typically plotted on a log-log to visualize the flicker regime. The slope in this yields the exponent β through , while the intercept provides the level , often denoted as h or related to the flicker coefficient K_f in models like S_v(f) = K_f / f^β. Fitting is performed via least-squares minimization to extract these parameters accurately, assuming stationarity. For non-stationary data exhibiting drifts, detrending via spline approximation removes low-frequency trends, producing residuals suitable for PSD computation and preventing bias in β estimation. The corner frequency f_c, marking the transition from flicker to white noise dominance, is determined by extrapolating the linear fits of the 1/f and flat regions on the log-log PSD plot and finding their intersection. Accurate determination requires sufficient frequency span and low noise floor; errors arise from low-frequency aliasing if anti-aliasing filters are inadequate, folding high-frequency components into the flicker band and inflating f_c estimates. Error analysis involves assessing statistical variance ε_r ≈ 1/√(2TΔf), where T is integration time and Δf is resolution bandwidth, emphasizing the need for fine Δf to minimize systematic deviations exceeding 10% near f_min. Parameter extraction extends to device-specific models, such as Hooge's empirical relation for resistance noise, S_R(f) = α_H V^2 / (N f), where α_H is the Hooge parameter and N is the total carrier number. Least-squares fitting of the to this form isolates α_H, typically in the range 10^{-6} to 10^{-3} for semiconductors, enabling comparison across devices. In amplifiers, flicker noise contributes to the overall ; the equivalent input noise is computed by integrating the over the , yielding RMS voltage v_{n,rms} ≈ v_{nw} √[f_c ln(f_c / f_L) + (f_H - f_c)], where v_{nw} is the white noise density, f_L and f_H are the lower and upper limits, and f_c is the corner . This integral quantifies the flicker contribution, often dominating below 10 Hz. Key challenges in flicker noise include the necessity for long times to achieve reliable low-frequency estimates; for frequencies below 1 Hz, durations of hours to days are required to reduce statistical error below 5%, limited by assumptions and environmental drifts. Software tools automate these processes: MATLAB's pwelch function implements with customizable windows and overlaps, while Python's library offers signal.welch for estimation and curve_fit for parameter extraction, facilitating reproducible analysis in research settings.

Mitigation Strategies

Reduction Techniques

Several techniques have been developed to suppress flicker noise, also known as 1/f noise, by shifting its spectral content away from the signal band or minimizing its generation at the source. These methods are particularly effective in low-frequency applications where flicker noise dominates over or . Chopping, or , involves multiplying the input signal with a periodic square wave at a higher , typically in the kHz range, to up-convert the low-frequency flicker noise to odd harmonics around the chopping frequency, where its power is significantly reduced due to the 1/f dependence. The modulated signal is then amplified and demodulated using phase-sensitive detection to recover the original signal while filtering out the up-converted noise with a . This technique effectively suppresses flicker noise in operational amplifiers and systems, achieving reductions of over 40 dB in some implementations. Correlated double sampling (CDS) is a sampling-based commonly used in switched-capacitor circuits and image sensors, where the signal is sampled twice—once immediately after to capture noise and offsets, and again after a fixed period to measure the signal plus noise—and their difference is computed to cancel low-frequency components, including and . By acting as a with a corner frequency determined by the sampling interval, CDS can attenuate 1/f noise by factors dependent on the sampling rate, often reducing it below levels in arrays. Auto-zeroing periodically samples and stores the amplifier's and flicker noise capacitors during a non-signal phase, then subtracts this stored value from the output during the signal phase, effectively averaging out low-frequency contributions over multiple cycles. This technique, akin to a sampled , reduces 1/f noise in continuous-time amplifiers but introduces switched noise that must be managed. Switched biasing complements auto-zeroing by periodically varying the bias currents to disrupt correlated trap states responsible for flicker noise, thereby suppressing random telegraph signal components that contribute to the 1/f spectrum, with demonstrated reductions in mm-wave mixers. AC coupling employs high-pass filters, typically RC networks, to block DC and sub-Hertz frequencies where flicker noise is prominent, allowing mid-frequency signals to pass while attenuating low-frequency noise without affecting the signal bandwidth above the cutoff. This simple passive method is widely used in sensor interfaces to reject baseline drift and 1/f contributions, though the cutoff frequency must be tuned below the signal band to avoid distortion, achieving effective noise suppression in ac-excited systems. At the device level, selecting materials with low flicker noise generation is crucial; for resistors, wire-wound or metal-film types exhibit negligible 1/f noise compared to carbon-composition or thick-film variants, which suffer from higher excess noise due to granular structures and contact effects. Foil resistors further minimize flicker through bulk metal construction, making them preferable in precision analog circuits where resistor noise would otherwise dominate the low-frequency spectrum.

Design Implementation

In amplifier design, increasing the gate area of MOSFETs reduces flicker noise by decreasing the flicker noise coefficient relative to the channel dimensions. The power spectral density of flicker noise in MOSFETs follows S_{i_d} = \frac{K_f I_d^\alpha}{f W L}, where K_f is the flicker noise coefficient, I_d is the drain current, f is frequency, W and L are channel width and length, and \alpha is typically 1 or 2; thus, larger W L directly lowers noise levels, as observed in power MOSFETs with wide channels where flicker noise is significantly suppressed compared to narrow-channel devices in low-power applications. Differential topologies further mitigate flicker noise by rejecting common-mode components, particularly in reducing upconversion to phase noise in oscillators, where matched pairs cancel correlated flicker contributions from symmetric disturbances. High-gain in amplifiers suppresses flicker noise at the output by reducing the overall while stabilizing the system, effectively lowering the contribution of input-stage flicker to the output . chopper-stabilized operational amplifiers exemplify this integration, employing to shift flicker noise to higher frequencies for filtering; examples include the OPA333 (10 µV , 125 kHz chopping) and OPA388 (5 µV , 200 kHz chopping), which eliminate 1/f noise through continuous internal but require careful impedance management to avoid charge injection artifacts. Process optimization during fabrication minimizes interface traps, a primary source of flicker noise, through tailored doping profiles and annealing techniques. Buried-channel MOSFETs, formed by to separate the conduction channel from the Si/SiO₂ interface, reduce carrier-trap interactions and yield spectral densities over 10 times lower than surface-channel devices at low drain currents (1–100 μA). Radical oxidation annealing at 400°C further passivates interface traps, lowering by a factor of 3 to approximately $2 \times 10^{16} cm⁻³ eV⁻¹ and eliminating mobility fluctuations that amplify flicker noise. Hydrogen annealing similarly reduces oxide trap by a factor of 3 in FinFETs, directly correlating with diminished low-frequency noise. Implementing these mitigations involves trade-offs, such as increased power consumption and circuit complexity from stabilization, which demands higher amplifiers and additional filtering to suppress tones at chopping frequencies, potentially raising overall by 20–50% in low-power designs. Circuit simulations using models with flicker noise sources are essential for evaluating these effects; the BSIM3 model incorporates flicker noise as S_{id} = \frac{K_f I_{ds}^{a_f}}{f^{a_f + e_f} C_{ox} L_{eff} W_{eff}}, enabling accurate prediction of noise in multistage amplifiers under varying bias conditions. Noise budgeting in low-noise designs follows guidelines emphasizing input-stage dominance, with flicker noise allocation targeting levels below 1 nV/√Hz at 10 Hz to ensure overall system performance; this involves optimizing bias currents and paralleling devices to minimize equivalent input noise while adhering to IEEE-referenced models for thermal and 1/f contributions.

Applications and Impacts

In Electronics and Circuits

Flicker noise significantly degrades the (SNR) in low-frequency electronic circuits, particularly those operating below a few hundred hertz, where it dominates over noise. In audio preamplifiers, this low-frequency noise introduces unwanted and , limiting the fidelity of signal amplification for high-quality audio reproduction. Similarly, in sensor interfaces and DC instrumentation amplifiers, flicker noise elevates the , reducing accuracy in applications requiring precise low-level signal detection, such as gauges or sensors. In oscillators, flicker noise contributes to through up-conversion mechanisms, extending the classic Leeson model to account for its 1/f spectral dependence, which becomes prominent close-in to the carrier and impacts timing stability in communication systems. In various electronic devices, flicker noise imposes fundamental limits on performance, particularly in precision analog components. For analog-to-digital converters (ADCs), it increases quantization noise at low frequencies, constraining effective resolution in data acquisition systems below the flicker corner frequency, often around 10-100 Hz. Operational amplifiers (op-amps) suffer from elevated input-referred noise due to flicker contributions from bias currents, degrading precision in feedback loops for instrumentation. In RF mixers, especially CMOS-based designs, flicker noise down-converts during frequency translation, raising the noise figure and compromising receiver sensitivity in low-IF architectures. As CMOS technology scales from 65 nm to 7 nm nodes, the flicker corner frequency shifts upward—typically from tens of Hz to several kHz or MHz—due to increased interface trap densities and reduced channel lengths, exacerbating these effects in scaled transistors. Accurate modeling of flicker noise is essential in circuit simulation tools like with , where it is incorporated as a current noise source in BSIM compact models using parameters such as for the 1/f power . This enables reliability analysis by simulating noise contributions across operating conditions, allowing designers to predict SNR degradation and optimize biasing to minimize up-conversion in mixed-signal ICs. For instance, SPICE-level simulations reveal how flicker noise propagates in op-amp chains, guiding layout choices to reduce parasitic effects. Case studies highlight flicker noise dominance in specific devices operating below 100 Hz. In accelerometers, such as capacitive lateral types, flicker noise from the readout circuitry and interfaces often exceeds mechanical-thermal noise at low frequencies, limiting resolution in vibration sensing for automotive or seismic applications. Photodetectors, including flexible organic variants, exhibit 1/f noise as the primary contributor below 100 Hz, arising from carrier trapping at interfaces, which reduces detectivity in low-light imaging or systems. Mitigation through chopper amplifiers yields substantial improvements, particularly in biomedical implants where low-power operation is critical. By modulating the signal to a higher (e.g., 1-10 kHz) and demodulating after amplification, chopper techniques shift flicker noise out of the , achieving up to 100-fold reduction in input-referred density—often from μV/√Hz to /√Hz levels—enabling high-SNR neural recording with minimal power overhead. This approach has been demonstrated in integrated front-ends for ECG and EEG acquisition, enhancing implant longevity and .

In Scientific and Engineering Fields

In , flicker noise manifests as plasma instabilities in (LIBS), leading to shot-to-shot fluctuations that degrade signal and limit detection sensitivity. These source fluctuations, often characterized by a 1/f power , arise from variations in laser- interactions and contribute to poor precision in . In quantum physics and superconducting devices, 1/f flux noise in SQUID-based superconducting qubits acts as a primary decoherence mechanism, constraining coherence times to microseconds and hindering scalable . This noise, typically on the order of 1–10 μΦ₀/√Hz at 1 Hz, originates from trapping and surface defects in the Josephson junctions. Similarly, in detectors like , unidentified 1/f noise components in the strain sensitivity curve below 300 Hz, stemming from electronic and suspension systems, impose limits on low-frequency signal detection and require advanced noise modeling for accurate astrophysical inferences. Biological signals exhibit 1/f characteristics as indicators of healthy system complexity, with (HRV) displaying spectra (α ≈ 1) in RR intervals for physiologically robust individuals, where deviations toward (α ≈ 0) or brown noise (α ≈ 2) signal . In (EEG), flicker noise dominates the power , reflecting synchronized neural dynamics, and its analysis via flicker-noise reveals underlying brain state transitions during cognitive tasks. Extending to neural networks, 1/f fluctuations emerge in both biological and modeled systems, promoting critical and long-range temporal correlations essential for adaptive information processing. In , 1/f noise appears in spectra of rotating machinery, where it signifies baseline healthy operation amid fluctuations, as observed in drivetrains during variable load conditions. This noise aids fault detection by contrasting with peaks from imbalances or bearings. In modeling, long-term atmospheric fluctuations follow 1/f scaling, capturing persistent patterns and improving simulations of decadal variability over purely random models. Recent advancements in hardware address flicker noise in neuromorphic , where memristor-based synapses exhibit 1/f resistance fluctuations that, while challenging inference accuracy, can be harnessed for to mimic biological variability. Mitigation strategies in low-Earth orbit satellite sensors, such as tone-based calibration for hyperspectral radiometers, suppress flicker noise from low-noise amplifiers, enhancing data fidelity for amid orbital dynamics.

References

  1. [1]
    [PDF] 1/f noise: a pedagogical review. - arXiv
    The observed spectral density of flicker noise is actually quite variable: it behaves like 1/f , where is in the range 0.5 ÷ 1.5, and usually this behavior ...
  2. [2]
    [PDF] Noise Sources in Bulk CMOS - MIT
    This recent literature supports number fluctuations as the primary source of flicker noise in. MOSFETs. Responding to this evidence, Hooge [25] has recently ...
  3. [3]
    [PDF] The generation and recognition of flicker noise
    semiconductor devices. It is interesting to note that flicker noise is often referred to as "semiconductor noise. ".
  4. [4]
    1/f (Flicker) Noise: A Brief Review - IEEE Xplore
    In this paper a review is given of the systems exhibiting I / f noise and the postulates researchers have made about its origin.
  5. [5]
    Noise Figure: Overview of Noise Measurement Methods - Tektronix
    Thermal noise can be considered to have a flat power spectral density out to 100 GHz or more before the quantum effects become dominant. Figure 8. Thermal ...
  6. [6]
    Small-Shot Effect and Flicker Effect | Phys. Rev.
    The Flicker Effect.—J. B. Johnson observed, under certain conditions (oxide coated and tungsten filaments, low frequencies, electron currents high but not ...Missing: history noise 1920s- 1940s<|separator|>
  7. [7]
    [PDF] Electronic noise: - the first two decades - No contents here
    The work of. Johnson at lower frequencies revealed the existence of the. "flicker effect,” which could be many times greater than the shot effect, as well as ...Missing: 1940s | Show results with:1940s
  8. [8]
    Flicker () noise: Equilibrium temperature and resistance fluctuations
    Jan 15, 1976 · We have measured the 1 f voltage noise in continuous metal films. At room temperature, samples of pure metals and bismuth (with a carrier ...
  9. [9]
    1/F Noise in Mosfets - SpringerLink
    Cheng, A unified model for the flicker noise in metal-oxide-semiconductor field-effect transistors, IEEE Trans. Electron Devices 37, 654-665 (1990). Article ...
  10. [10]
    Evolution of 1 / f Flux Noise in Superconducting Qubits with Weak ...
    Recent progress in superconducting devices for quantum information has highlighted the need to mitigate sources of qubit decoherence, driving a renewed ...
  11. [11]
    [2401.11989] 1/f noise in quantum nanoscience - arXiv
    Jan 22, 2024 · Fundamental issues of 1/f noise in quantum nanoscience are reviewed starting from basic statistical noise processes.Missing: advances origins 2020-2025
  12. [12]
    Electronic noise—From advanced materials to quantum technologies
    Jan 29, 2024 · The topics covered in the Special Issue include thermal noise and shot noise in advanced materials and devices; low-frequency 1/f noise and ...
  13. [13]
    [PDF] A Study of Flicker Noise in MOSFETS. - DTIC
    Writing this review has stimulated our thinking and has shaped our 1/f noise program. 3. Theses completed and (or) defended during the period. Mr. S. K. Kim ...
  14. [14]
    Universality of trap-induced mobility fluctuations between 1/f noise ...
    Jun 6, 2023 · Therefore, a unified flicker noise model approach was adopted, called CNF/CMF: the carrier number with correlated mobility fluctuations. The ...
  15. [15]
    Flicker Noise - an overview | ScienceDirect Topics
    Flicker noise is also called 1/f noise. Its origin is one of the oldest unsolved problems in physics. It is pervasive in nature and in many human endeavors. It ...Missing: etymology | Show results with:etymology
  16. [16]
    On the Hooge relation in semiconductors and metals - AIP Publishing
    Jul 30, 2009 · The relation known as the Hooge formula was proposed 40 years ago to describe the 1 / f noise in metals and semiconductors.Missing: flicker | Show results with:flicker
  17. [17]
  18. [18]
    Managing Noise in the Signal Chain, Part 1 - Analog Devices
    Aug 7, 2014 · Pink noise is characterized by a spectral density that increases with decreasing frequency. It contains equal amounts of energy in each decade ...
  19. [19]
    [PDF] Noise models for diodes and transistors - EE@IITM
    ▻ pn junctions and BJTs - shot noise, flicker noise, burst noise. ▻ MOSFETs - flicker noise, thermal noise in strong inversion, shot noise in weak ...
  20. [20]
    [PDF] Noise in Semiconductor Devices - Auburn University
    Jun 22, 2010 · The most important sources of noise are thermal noise, shot noise, generation-recombination noise,. 1/f noise (flicker noise), 1/f 2 noise, ...
  21. [21]
    Noise from Systems in Thermal Equilibrium | Phys. Rev. Lett.
    1 f Noise from Systems in Thermal Equilibrium. Richard F. Voss and John Clarke. Department of Physics, University of California, Berkeley ...Missing: flicker non-<|control11|><|separator|>
  22. [22]
    On low frequency and 1/f noise from diffusion like processes
    The noise spectrum resulting from diffusion like processes is calculated in two and three dimensions for two different forms of free energy fluctuation.
  23. [23]
    Self-organized criticality: An explanation of the 1/f noise
    Jul 27, 1987 · We show that dynamical systems with spatial degrees of freedom naturally evolve into a self-organized critical point. Flicker noise, or 1/f ...
  24. [24]
    1/f Noise in Semiconductor Lasers and Its Reduction
    A combination of optical and electrical feedback to suppress frequency noise of semiconductor laser is studied theoretically by adding a 1/f noise source.
  25. [25]
    [PDF] 1/f noise in turbulent flows - arXiv
    May 31, 2016 · Abstract We report the experimental observation of 1/f fluctuations in three different turbulent flow configurations: the large scale ...Missing: river | Show results with:river
  26. [26]
    Model for Flux Noise in SQUIDs and Qubits | Phys. Rev. Lett.
    Jun 27, 2007 · We propose a model for 1/f flux noise in superconducting devices (f is frequency). The noise is generated by the magnetic moments of electrons in defect states.
  27. [27]
    Self-organized criticality | Phys. Rev. A
    Jul 1, 1988 · The temporal ''fingerprint'' of the self-organized critical state is the presence of flicker noise or 1/f noise; its spatial signature is the ...
  28. [28]
    [PDF] Noise Analysis in Operational Amplifier Circuits - Texas Instruments
    The terms 4kTR and 4kT/R are voltage and current power densities having units of V2/Hz and A2/Hz. Flicker Noise. Flicker noise is also called 1/f noise. It ...
  29. [29]
    [PDF] A Statistical Flicker Noise Analytical Model in Scaled Bulk MOSFETs
    Jan 27, 2009 · This paper presents a statistical flicker noise analytical model for scaled bulk MOSFETs, which is a dominant noise source at low frequencies ...Missing: S_v = K_f /
  30. [30]
    1/ƒ noise is no surface effect - ScienceDirect.com
    1/ƒ Noise is inversely proportional to the total number of mobile charge carriers in homogeneous samples. This excludes surface effects as the main source ...
  31. [31]
    1/f (Flicker Noise) Modeling - People
    The power noise spectrum of the base current is simply amplified by a factor h2fe at the output (hfe is the small signal current gain). Having considered this, ...
  32. [32]
    Systematical Investigation of Flicker Noise in 14 nm FinFET Devices ...
    Nov 14, 2023 · In this work, we systematically and statistically study the flicker noise characteristics of 14 nm FinFET devices. It is found that the channel ...Missing: contaminants | Show results with:contaminants
  33. [33]
    Understanding Op Amp Noise in Audio Circuits - Texas Instruments
    Flicker noise, or 1/f noise, is considered to be in the low frequency range; that is, frequencies less than 1kHz. 1/f noise has a slope of one divided by the ...
  34. [34]
    A 2-stage recursive receiver optimized for low flicker noise corner
    An implementation in 130 nm CMOS provides 59.6 dB conversion gain for an RF of 960 MHz, and 8.2 dB DSB-NF. The measured flicker noise corner frequency is 100 ...
  35. [35]
    [PDF] MT-048: Op Amp Noise Relationships - Analog Devices
    Equation 2 can be used to calculate the total rms noise in the bandwidth 0.1 to 10 Hz by letting FL = 0.1 Hz, FH = 10 Hz, FC = 0.7 Hz, vnw = 10 nV/√Hz. The ...
  36. [36]
  37. [37]
    Understanding and Eliminating 1/f Noise - Analog Devices
    1/f noise is low frequency noise for which the noise power is inversely proportional to the frequency. 1/f noise has been observed not only in electronics, but ...Missing: timeline milestones
  38. [38]
    Temperature dependence of 1∕f noise mechanisms in silicon ...
    The exponents of the 1∕fβ spectra all lie in the range 0.8<β<1.2. The flattening of the noise spectra is due to background noise from the measurement setup.
  39. [39]
    Tests of Gaussian statistical properties of 1/f noise - AIP Publishing
    Oct 1, 1983 · One carbon resistor showed clear non‐Gaussian behavior. The significance of the results for models of the origins of 1/f noise is discussed.Missing: assumption | Show results with:assumption
  40. [40]
    On the Autocorrelation Function of 1/f Noises - MDPI
    1/f noises have a power spectrum of S(f) ~ 1/f^β. This paper provides an analytical derivation of their autocorrelation function C(k), which was previously ...Missing: tau | Show results with:tau
  41. [41]
    1/fβ noise in a model for weak ergodicity breaking - ScienceDirect
    Oct 5, 2010 · In systems with weak ergodicity breaking, the equivalence of time averages and ensemble averages is known to be broken.
  42. [42]
    [PDF] Handbook of Frequency Stability Analysis
    Feb 5, 2018 · White noise has a flat spectral density (by analogy to white light). Flicker noise has an f-1 spectral density, and is called pink or red ...
  43. [43]
    Low frequency noise measurements: Applications, methodologies ...
    Aug 9, 2025 · The analysis of the low frequency noise generated in solid state devices represents a key factor in the era of VLSI technology.<|control11|><|separator|>
  44. [44]
    (PDF) DEDICATED INSTRUMENTATION FOR HIGH SENSITIVITY, LOW FREQUENCY NOISE MEASUREMENT SYSTEMS
    **Summary of Dedicated Instrumentation for Low Frequency Noise Measurement Systems**
  45. [45]
    (PDF) A correlation noise spectrometer for flicker ... - ResearchGate
    PDF | We present a high-resolution digital correlation spectrum analyzer for the measurement of low frequency resistance fluctuations in graphene.
  46. [46]
    [PDF] About Lock-In Amplifiers - thinkSRS.com
    The Lock-In as a Noise Measurement Device. Lock-in amplifiers can be used to measure noise. Noise measurements are generally used to characterize components.
  47. [47]
  48. [48]
  49. [49]
  50. [50]
  51. [51]
    Mobility-Dependent Low-Frequency Noise in Graphene Field-Effect ...
    Sep 13, 2011 · It follows from the model that the Hooge parameter would be reduced by reducing charge trapping and the number of scattering centers, which is ...
  52. [52]
  53. [53]
  54. [54]
  55. [55]
    Correlated Double Sampling (CDS) for Solid-State Image Sensors
    Aug 23, 2023 · ▷ Filter the 1/f noise - so-called 'flicker' noise. ▷ Restore the system DC level. ▷ Remove the fixed pattern noise (FPN) – switch feedthroughs,.
  56. [56]
    Neural Recording Analog Front-End Noise Reduction with Digital ...
    Correlated double-sampling (CDS) is a method that can be used to reduce low frequency noise. Conventionally implemented as an analog reset of the amplifier ...
  57. [57]
    [PDF] Noise optimization of the source follower of a CMOS pixel using ...
    To analyze the 1/f noise in CIS we first discuss the CDS effect on 1/f noise. CDS as a noise reduction technique is indispensable in image sensor to reduce kTC ...
  58. [58]
    [PDF] Low-Frequency Noise Reduction Using In-Pixel Chopping To ... - arXiv
    Nov 26, 2018 · The proposed in-pixel chopping technique is used to reduce the low-frequency or 1/f noise of the source follower (SF) in an active pixel sensor ...
  59. [59]
    [PDF] Trend Investigation of Biopotential Recording Front-End Channels ...
    Several methods such as autozeroing, chopping, and switched biasing can be used to reduce the flicker noise [360]–[362], but among them, the chopping technique.
  60. [60]
  61. [61]
    A Chopper Stabilized Current-Feedback Instrumentation Amplifier ...
    Feb 4, 2019 · The proposed design includes an ac-coupled chopper-stabilized CFIA to reduce 1/f noise. It also has a switched-capacitor integrator to.
  62. [62]
    [1012.5898] Low noise constant current source for bias dependent ...
    Usually a wire wound or a metal film resistor 10 times the sample resistance with negligible level of flicker noise is used as the ballast. Scofield However ...
  63. [63]
    Precision Resistor - an overview | ScienceDirect Topics
    Noise (100 Hz to 1 MHz), −35 db (max). *: −55°C to 125°C. Nichrome resistors are ... Poly-Si resistors suffer from low frequency (flicker) noise due to ...
  64. [64]
    Experimental characterization of low-frequency noise in power ...
    Since vertical power MOSFETs typically have very large channel width, flicker noise is expected to be very low when compared to the noise levels associated ...
  65. [65]
    Differential tuning oscillators with reduced flicker noise upconversion
    The adoption of differential tuning in oscillators provides cancellation of common-mode disturbances, and thus, it is expected to lower phase noise and ...
  66. [66]
    1/F Noise: Flicker Noise Impact and Mitigation Strategies
    Oct 9, 2023 · Flicker noise manifests in various electronic components due to irregularities within the conduction path, coupled with noise from bias currents ...
  67. [67]
    [PDF] Optimizing Chopper Amplifier Accuracy (Rev. A) - Texas Instruments
    Flicker noise can be thought of as a variation of input offset voltage versus time. Thus, chopper amplifiers eliminate 1/f noise.
  68. [68]
    New Processes and Technologies to Reduce the Low‐Frequency ...
    Oct 5, 2016 · The chapter is intended to provide the reader with means to reduce low‐frequency noise in Metal-Oxide-Semiconductor Field-Effect-Transistor ...
  69. [69]
    Hydrogen annealing effect on DC and low-frequency noise ...
    Aug 10, 2025 · The low-frequency noise characteristics indicate that the oxide trap density is reduced by a factor of 3 due to annealing. These results suggest ...
  70. [70]
    [PDF] CHAPTER 8: Noise Modeling
    There exist two models for flicker noise modeling. One is called SPICE2 flicker noise model; the other is BSIM3 flicker noise model [35-36]. The flicker noise ...
  71. [71]
    [PDF] Fundamentals of low-noise analog circuit design - Marshall Leach
    This paper covers noise fundamentals, noise models for devices, calculating noise performance, and techniques for minimizing noise in circuit design.
  72. [72]
    Noise in Audio Amplifiers - Elliott Sound Products
    Flicker noise is a low frequency effect, and as such is not so much of a problem with audio circuits. It becomes worse as frequency is reduced, and this can ...
  73. [73]
  74. [74]
    [PDF] Fundamentals of Precision ADC Noise Analysis - Texas Instruments
    1/f (pink, flicker) noise, which is low-frequency noise that has a power density inversely proportional to frequency. • Popcorn (burst) noise, which is low ...
  75. [75]
    Noise in RF-CMOS mixers: a simple physical model - ResearchGate
    Aug 9, 2025 · Flicker noise in the mixer of a zero- or low-intermediate frequency (IF) wireless receiver can compromise overall receiver sensitivity.<|control11|><|separator|>
  76. [76]
    Modeling of low‐frequency noise in advanced CMOS devices
    Feb 16, 2015 · In this paper, we review in detail the evolution of the LFN level and its variability in all the major CMOS technologies, from 0.5 μm to 20 nm.
  77. [77]
    [PDF] Flicker Noise Formulations in Compact Models - Ken Kundert
    Abstract—This article shows how to properly define modulated flicker noise in Verilog-A compact models, and how a simulator should handle flicker noise for ...Missing: seminal K_f
  78. [78]
    An Improved Flicker Noise Model for Circuit Simulations
    Compact flicker noise models used in SPICE circuit simulators are derived from the seminal BSIM unified noise model. In this paper, we show that use of this ...
  79. [79]
    Monolithic Low Noise and Low Zero-g Offset CMOS/MEMS ... - NIH
    The accelerometer operates at low frequency. Hence, flicker noise is dominant. Due to the process limitation, the sensing capacitor of the accelerometers at 1 g ...Missing: dominates | Show results with:dominates
  80. [80]
    Optoelectrical and low-frequency noise characteristics of flexible ...
    Although the low-frequency noise of the device was dominated by 1/f noise, the 1/f law is valid only up to 100 Hz. The measured noise decreased as 1/f1.3 above ...
  81. [81]
    Noise Efficient Integrated Amplifier Designs for Biomedical ... - MDPI
    The chopper technique can avoid the flicker noise bandwidth but comes with the aforementioned limitations in terms of current noise, power, and design overhead.
  82. [82]
    (PDF) √ Hz Chopper stabilized Amplifier for Biomedical Application ...
    Oct 6, 2024 · The amplifier, which is based on an original topology, embodies chopper modulation for offset and flicker noise reduction. The paper ...Missing: 100x implants
  83. [83]
    Laser-induced XUV spectroscopy (LIXS): From fundamentals to ...
    Laser-induced breakdown spectroscopy (LIBS) is a rapid in-situ microanalytical technique. Affected by poor precision, due to plasma flicker noise, ...
  84. [84]
    Signal and noise in Laser Induced Breakdown Spectroscopy
    Aug 6, 2025 · LIBS users often report poor repeatability of the signal, due to shot-to-shot fluctuations, and consequent not satisfactory limits of detection.Missing: flicker instabilities
  85. [85]
    Characterizing and optimizing qubit coherence based on SQUID ...
    Feb 21, 2020 · The dominant source of decoherence in contemporary frequency-tunable superconducting qubits is 1/f flux noise. To understand its origin and find ...
  86. [86]
    Complexity and Disorder of 1/ f α Noises - PubMed
    Oct 4, 2020 · Accordingly, we have found that the 1/fα noises for α around 1.5 are equivalent to the RR interval series of healthy subjects.
  87. [87]
    Analysis of EEG signal by flicker-noise spectroscopy - PubMed Central
    Flicker-noise spectroscopy (FNS) is a general phenomenological approach to analyzing dynamics of complex nonlinear systems by extracting information ...
  88. [88]
    Critical synchronization and 1/f noise in inhibitory/excitatory rich-club ...
    Feb 4, 2019 · 1/f fluctuations (pink noise) represent the fractal temporal properties of neural networks that exhibit long-range memory.
  89. [89]
    (PDF) Observations and modeling of 1/f-noise in weather and climate
    Aug 10, 2025 · The presence of 1/f power spectra in weather and climate is noteworthy: (i) In the tropical atmosphere 1/f scaling ranging from hours to weeks ...Missing: 2020s | Show results with:2020s
  90. [90]
    Transforming memristor noises into computational innovations
    Jul 14, 2025 · In practice, flicker noise and RTN often significantly impact device behavior, reducing the readout margin and causing significant read noises ...
  91. [91]
    A Tone-Based Flicker Noise Mitigation Technique for Broadband ...
    High-frequency microwave radiometers with low-noise amplifier (LNA) front-ends commonly suffer from gain instability, or so-called "flicker" noise.