Showing papers on "Noise measurement published in 1999"

Oscillator phase noise: a tutorial

Abstract: Linear time-invariant (LTI) phase noise theories provide important qualitative design insights but are limited in their quantitative predictive power. Part of the difficulty is that device noise undergoes multiple frequency translations to become oscillator phase noise. A quantitative understanding of this process requires abandoning the principle of time invariance assumed in most older theories of phase noise. Fortunately, the noise-to-phase transfer function of oscillators is still linear, despite the existence of the nonlinearities necessary for amplitude stabilization. In addition to providing a quantitative reconciliation between theory and measurement, the time-varying phase noise model presented in this tutorial identifies the importance of symmetry in suppressing the upconversion of 1/f noise into close-in phase noise, and provides an explicit appreciation of cyclostationary effects and AM-PM conversion. These insights allow a reinterpretation of why the Colpitts oscillator exhibits good performance, and suggest new oscillator topologies. Tuned LC and ring oscillator circuit examples are presented to reinforce the theoretical considerations developed. Simulation issues and the accommodation of amplitude noise are considered in appendixes.

Wavelet-based Rician noise removal for magnetic resonance imaging

Abstract: It is well known that magnetic resonance magnitude image data obey a Rician distribution. Unlike additive Gaussian noise, Rician "noise" is signal-dependent, and separating signal from noise is a difficult task. Rician noise is especially problematic in low signal-to-noise ratio (SNR) regimes where it not only causes random fluctuations, but also introduces a signal-dependent bias to the data that reduces image contrast. This paper studies wavelet-domain filtering methods for Rician noise removal. We present a novel wavelet-domain filter that adapts to variations in both the signal and the noise.

The CFAR adaptive subspace detector is a scale-invariant GLRT

Abstract: The constant false alarm rate (CFAR) matched subspace detector (CFAR MSD) is the uniformly most-powerful-invariant test and the generalized likelihood ratio test (GLRT) for detecting a target signal in noise whose covariance structure is known but whose level is unknown. Previously, the CFAR adaptive subspace detector (CFAR ASD), or adaptive coherence estimator (ACE), was proposed for detecting a target signal in noise whose covariance structure and level are both unknown and whose covariance structure is estimated with a sample covariance matrix based on training data. We show here that the CFAR ASD is GLRT when the test measurement is not constrained to have the same noise level as the training data, As a consequence, this GLRT is invariant to a more general scaling condition on the test and training data than the well-known GLRT of Kelly (1986).

Alpha-stable modeling of noise and robust time-delay estimation in the presence of impulsive noise

Abstract: A new representation of audio noise signals is proposed, based on symmetric /spl alpha/-stable (S/spl alpha/S) distributions in order to better model the outliers that exist in real signals. This representation addresses a shortcoming of the Gaussian model, namely, the fact that it is not well suited for describing signals with impulsive behavior. The /spl alpha/-stable and Gaussian methods are used to model measured noise signals. It is demonstrated that the /spl alpha/-stable distribution, which has heavier tails than the Gaussian distribution, gives a much better approximation to real-world audio signals. The significance of these results is shown by considering the time delay estimation (TDE) problem for source localization in teleimmersion applications. In order to achieve robust sound source localization, a novel time delay estimation approach is proposed. It is based on fractional lower order statistics (FLOS), which mitigate the effects of heavy-tailed noise. An improvement in TDE performance is demonstrated using FLOS that is up to a factor of four better than what can be achieved with second-order statistics.

Characterizing human perceptual inefficiencies with equivalent internal noise.

Abstract: A widely used method for characterizing and comparing inefficiencies in perceptual processes is the method of equivalent internal noise—the amount of random internal noise necessary to produce the degree of inefficiency exhibited by the perceptual system in processing [J. Opt. Soc. Am.46, 634 (1956)]. One normally estimates the amount of equivalent internal noise by systematically increasing the amount of external noise added to the signal stimulus and observing how threshold—signal stimulus energy required for an observer to maintain a given performance level—depends on the amount of external noise. In a variety of perceptual tasks, a simple noisy linear amplifier model [ D. Pelli , Ph.D. dissertation (University of Cambridge, Cambridge, UK1981)] has been utilized to estimate the equivalent internal noise Ninternal by fitting of the relation between threshold contrast cτ and external noise Next at a single (d′) performance level: cτ2=(d′/β)2(Next2+N internal2). This model makes a strong prediction: Independent of observer and external noise contrast, the ratio between two thresholds at each external noise level is equal to the ratio of the two corresponding d′ values. To our knowledge, this potential test for the internal consistency of the model had never been examined previously. In this study we estimated threshold ratios between multiple performance levels at various external noise contrasts in two different experiments: Gabor orientation identification, and Gabor detection. We found that, in both identification and detection, the observed threshold ratios between different performance levels departed substantially from the d′ ratio predicted by the simple noisy linear amplifier model. An elaborated perceptual template model [Vision Res.38, 1183 (1998)] with nonlinear transducer functions and multiplicative noise in addition to the additive noise in the simple linear amplifier model leads to a substantially better description of the data and suggests a reinterpretation of earlier results that relied on the simple noisy linear amplifier model. The relationship of our model and method to other recent parallel and independent developments [J. Opt. Soc. Am. A14, 2406 (1997)] is discussed.

Effect of Directional Array Size on the Measurement of Airframe Noise Components

Abstract: A study was conducted to examine the effects of overall size of directional (or phased) arrays on the measurement of aeroacoustic components An airframe model was mounted in the potential core of an open-jet windtunnel, with the directional arrays located outside the flow in an anechoic environment Two array systems were used; one with a solid measurement angle that encompasses 316 degrees of source directivity and a smaller one that encompasses 72 degrees The arrays, and sub-arrays of various sizes, measured noise from a calibrator source and flap edge model setups In these cases, noise was emitted from relatively small, but finite size source regions, with intense levels compared to other sources Although the larger arrays revealed much more source region detail, the measured source levels were substantially reduced due to finer resolution compared to that of the smaller arrays To better understand the measurements quantitatively, an analytical model was used to define the basic relationships between array to source region sizes and measured output level Also, the effect of noise scattering by shear layer turbulence was examined using the present data and those of previous studies Taken together, the two effects were sufficient to explain spectral level differences between arrays of different sizes An important result of this study is that total (integrated) noise source levels are retrievable and the levels are independent of the array size as long as certain experimental and processing criteria are met The criteria for both open and closed tunnels are discussed The success of special purpose diagonal-removal processing in obtaining integrated results is apparently dependent in part on source distribution Also discussed is the fact that extended sources are subject to substantial measurement error, especially for large arrays

Estimation of the noisy component of anatomical backgrounds.

Abstract: The knowledge of the relationship that links radiationdose and image quality is a prerequisite to any optimization of medicaldiagnostic radiology. Image quality depends, on the one hand, on the physical parameters such as contrast, resolution, and noise, and on the other hand, on characteristics of the observer that assesses the image. While the role of contrast and resolution is precisely defined and recognized, the influence of image noise is not yet fully understood. Its measurement is often based on imaging uniform test objects, even though real images contain anatomical backgrounds whose statistical nature is much different from test objects used to assess system noise. The goal of this study was to demonstrate the importance of variations in background anatomy by quantifying its effect on a series of detection tasks. Several types of mammographic backgrounds and signals were examined by psychophysical experiments in a two-alternative forced-choice detection task. According to hypotheses concerning the strategy used by the human observers, their signal to noise ratio was determined. This variable was also computed for a mathematical model based on the statistical decision theory. By comparing theoretical model and experimental results, the way that anatomical structure is perceived has been analyzed. Experiments showed that the observer’s behavior was highly dependent upon both system noise and the anatomical background. The anatomy partly acts as a signal recognizable as such and partly as a pure noise that disturbs the detection process. This dual nature of the anatomy is quantified. It is shown that its effect varies according to its amplitude and the profile of the object being detected. The importance of the noisy part of the anatomy is, in some situations, much greater than the system noise. Hence, reducing the system noise by increasing the dose will not improve task performance. This observation indicates that the tradeoff between dose and image quality might be optimized by accepting a higher system noise. This could lead to a better resolution, more contrast, or less dose.

A new look at impact ionization-Part II: Gain and noise in short avalanche photodiodes

Abstract: For Part I see R.J. McIntyre, ibid., vol.46, no.8, pp.1623-31 (1999). In Part I, a new theory for impact ionization that utilizes history-dependent ionization coefficients to account for the nonlocal nature of the ionization process has been described. In this paper, we will review this theory and extend it with the assumptions that are implicitly used in both the local-field theory in which the ionization coefficients are functions only of the local electric field and the new one. A systematic study of the noise characteristics of GaAs homojunction avalanche photodiodes with different multiplication layer thicknesses is also presented. It is demonstrated that there is a definite "size effect" for thin multiplication regions that is not well characterized by the local-field model. The new theory, on the other hand, provides very good fits to the measured gain and noise. The new ionization coefficient model has also been validated by Monte Carlo simulations.

Apparatus and method for noise attenuation in a speech recognition system

Abstract: The noise suppressor utilizes statistical characteristics of the noise signal to attenuate amplitude values of the noisy speech signal that have a probability of containing noise. In one embodiment, the noise suppressor utilizes an attenuation function having a shape determined in part by a noise average and a noise standard deviation. In a further embodiment, the noise suppressor also utilizes an adaptive attenuation coefficient that depends on signal-to-noise conditions in the speech recognition system.

ECG noise filtering using wavelets with soft-thresholding methods

Abstract: We analyze algorithms for filtering white gaussian noise and 50 Hz power line noise from ECG signals. We used several wavelets to study their effect and efficiency in the filtering process. To deal with these different kinds of noises we used two distinct soft-thresholding techniques: the Donoho's statistical threshold estimator and a method developed by us. This last method exploits one of the wavelet processing main features: time-frequency relation. The de-noising methods led to good filtering results: noise reduction with only minor change of the ECG waveforms as confirmed by the high correlation values between the processed signal and the original one. These good results are due to a wavelet advantage over classical filtering-time-frequency relation-enabling the possibility of filtering noise in the same frequency band of the ECG signal with minimal interference.

Wavelet-domain filtering for photon imaging systems

Abstract: Many imaging systems rely on photon detection as the basis of image formation. One of the major sources of error in these systems is Poisson noise due to the quantum nature of the photon detection process. Unlike additive Gaussian white noise, the variance of Poisson noise is proportional to the underlying signal intensity, and consequently separating signal from noise is a very difficult task. In this paper, we perform a novel gedankenexperiment to devise a new wavelet-domain filtering procedure for noise removal in photon imaging systems. The filter adapts to both the signal and the noise, and balances the trade-off between noise removal and excessive smoothing of image details. Designed using the statistical method of cross-validation, the filter is simultaneously optimal in a small-sample predictive sum of squares sense and asymptotically optimal in the mean-square-error sense. The filtering procedure has a simple interpretation as a joint edge detection/estimation process. Moreover, we derive an efficient algorithm for performing the filtering that has the same order of complexity as the fast wavelet transform itself. The performance of the new filter is assessed with simulated data experiments and tested with actual nuclear medicine imagery.

Method and apparatus for enhancing noise-corrupted speech

Abstract: A noise suppression device receives data representative of a noise-corrupted signal which contains a speech signal and a noise signal, divides the received data into data frames, and then passes the data frames through a pre-filter to remove a dc-component and the minimum phase aspect of the noise-corrupted signal. The noise suppression device appends adjacent data frames to eliminate boundary discontinuities, and applies fast Fourier transform to the appended data frames. A voice activity detector of the noise suppression device determines if the noise-corrupted signal contains the speech signal based on components in the time domain and the frequency domain. A smoothed Wiener filter of the noise suppression device filters the data frames in the frequency domain using different sizes of a window based on the existence of the speech signal. Filter coefficients used for Wiener filter are smoothed before filtering. The noise suppression device modifies magnitude of the time domain data based on the voicing information outputted from the voice activity detector.

Wide band AC power line characterization

Abstract: This paper presents data characterizing the household AC power line in the 1-60 MHz band. Two types of measurements were performed: transmission and noise sampling. The transmission measurements were done by using the impulse channel sounding method, so both the line attenuation and the delay spread were obtained. The noise measurements include: power line background noise, appliance noise, and noise sampled over a 24 hour period. Statistical characteristics of the delay spread, frequency response and noise can be extracted from the data and used in the design of AC power line based communications systems.

Towards true crosstalk noise analysis

Abstract: Accurate noise analysis is currently of significant concern to high-performance designs, and the number of signals susceptible to noise effects will certainly increase in smaller process geometries. Our approach uses a combination of temporal and functional information to eliminate false transition combinations and thereby overcome insufficiencies in static noise analysis. A similar idea arises in timing analysis where functional and timing information is used to eliminate false paths. The goal of our work is to develop an algorithm, software tool, and noise analysis flow that provide an accurate and conservative approach to noise analysis. In particular, this paper proposes an approach to identifying a pair of vectors that exercises the maximum crosstalk noise.

Theoretical noise reduction limits of the generalized sidelobe canceller (GSC) for speech enhancement

Abstract: We present an analysis of the generalized sidelobe canceller (GSC). It can be shown that the theoretical limits of the noise reduction performance depend only on the auto- and cross-spectral densities of the input signals. Furthermore, we compute the limits of the noise reduction performance for the theoretically determined diffuse noise field, which is an approximation for reverberant rooms. Our results show that the GSC cannot reduce noise further than 1 dB. These results were verified by simulation of reverberant environments. Only in sound-proof rooms with a reverberation time less than 100 ms the GSC performs well.

Method of noise reduction for speech codecs

Abstract: An improved noise reduction algorithm is provided, as well as a voice activity detector, for use in a voice communication system. The voice activity detector allows for a reliable estimate of noise and enhancement of noise reduction. The noise reduction algorithm and voice activity detector can be implemented integrally in an encoder or applied independently to speech coding application. The voice activity detector employs line spectral frequencies and enhanced input speech which has undergone noise reduction to generate a voice activity flag. The noise reduction algorithm employs a smooth gain function determined from a smoothed noise spectral estimate and smoothed input noisy speech spectra. The gain function is smoothed both across frequency and time in an adaptive manner based on the estimate of the signal-to-noise ratio. The gain function is used for spectral amplitude enhancement to obtain a reduced noise speech signal. Smoothing employs critical frequency bands corresponding to the human auditory system. Swirl reduction is performed to improve overall human perception of decoded speech.

Noise suppression for low bitrate speech coder

Abstract: Noise is suppressed in an input signal that carries a combination of noise and speech. The input signal is divided (10) into signal blocks, which are processed (14) to provide an estimate of a short-time perceptual band spectrum of the input signal. A determination is made (16) at various points in time as to whether the input signal is carrying noise only or a combination of noise and speech. When the input signal is carrying noise only, the corresponding estimated short-time perceptual band spectrum of the input signal is used to update an estimate (18) of a long term perceptual band spectrum of the noise. A noise suppression frequency response is then determined (20) based on the estimate of the long term perceptual band spectrum of the noise and the short-time perceptual band spectrum of the input signal, and used to shape (24) a current block of the input signal in accordance with the noise suppression frequency response.

An adaptive spatial diversity receiver for non-Gaussian interference and noise

Abstract: Standard linear diversity combining techniques are not effective in combating fading in the presence of non-Gaussian noise. An adaptive spatial diversity receiver is developed for wireless communication channels with slow, flat fading and additive non-Gaussian noise. The noise is modeled as a mixture of Gaussian distributions and the expectation-maximization (EM) algorithm is used to derive estimates for the model parameters. The transmitted signals are detected using a likelihood ratio test based on the parameter estimates. The new adaptive receiver converges rapidly, its bit error rate performance is very close to optimum when relatively short training sequences are used, and it appears to be relatively insensitive to mismatch between the noise model and the actual noise distribution. Simulation results are included that illustrate various aspects of the adaptive receiver performance.

Noise spectrum tracking for speech enhancement

Abstract: A spectrum-based speech enhancement system estimates and tracks the noise spectrum of a mixed speech and noise signal. The system frames and windows a digitized signal and applies the frames to a fast Fourier transform processor to generate discrete Fourier transformed (DFT) signals representing the speech plus noise signal. The system calculates the power spectrum of each frame. The speech enhancement system employs a leaky integrator that is responsive to identified noise-only components of the signal. The leaky integrator has an adaptive time-constant which compensates for non-stationary environmental noise. In addition, the speech enhancement system identified noise-only intervals by using a technique that monitors the Teager energy of the signal. The transition between noise-only signals and speech plus noise signals is softened by being made non-binary. Once the noise spectrum has been estimated, it is used to generate gain factors that multiply the DFT signals to produce noise-reduced DFT signals. The gain factors are generated based on an audible noise threshold. The method generates audible a priori and a posteriori signal to noise ratio signals and then calculates audible gain signals from these values.

System, method and apparatus for cancelling noise

Abstract: A threshold detector precisely detects the positions of the noise elements, even within continuous speech segments, by determining whether frequency spectrum elements, or bins, of the input signal are within a threshold set according to current and future minimum values of the frequency spectrum elements. In addition, the threshold is continuously set and initiated within a predetermined period of time. The estimate magnitude of the input audio signal is obtained using a multiplying combination of the real and imaginary part of the input in accordance with the higher and lower values between the real and imaginary part of the signal. In order to further reduce instability of the spectral estimation, a two-dimensional smoothing is applied to the signal estimate using neighboring frequency bins and an exponential average over time. A filter multiplication effects the subtraction thereby avoiding phase calculation difficulties and effecting full-wave rectification which further reduces artifacts. Since the noise elements are determined within continuous speech segments, the noise is canceled from the audio signal nearly continuously thereby providing excellent noise cancellation characteristics. Residual noise reduction reduces the residual noise remaining after noise cancellation. Implementation may be effected in various noise canceling schemes including adaptive beamforming and noise cancellation using computer program applications installed as software or hardware.

Adaptive two-threshold method for discriminating noise from speech in a communication signal

Abstract: A method of discriminating noise and voice energy in a communication signal. A signal is measured in a plurality of block periods, which are sampled to obtain a measurement of the block energy value for the signal. The blocks are compared to a noise threshold and to a voice threshold to discriminate between noise and voice. The thresholds for noise and voice are periodically updated based on the minimum and maximum energy levels measured for block energies. In a preferred embodiment, the voice energy threshold and noise energy threshold values are updated according to a formula where the revised thresholds are based upon a factor of the minimum and maximum energy levels of the current block and the most recent past block and the average energy of the previous blocks. Updating of threshold levels allows for more accurate estimation of noise and voice during changes in either noise, voice or both to avoid missclassification of noise and/or voice.

Accurate on-chip interconnect evaluation: a time-domain technique

Abstract: This paper describes an on-chip sampling and measurement technique for accurate (<15 ps) evaluation of interconnect delays and coupled noise. We have used this nonintrusive time-domain technique to extract in situ driver/receiver waveforms, propagation delays, and coupled noise in 120 interconnect structures. The effects studied include multiple AC returns through active devices, gridded planes on adjacent layers, via impedances, variable driver impedances, and noise in bus structures. The results provide a comprehensive evaluation of interconnect delays and noise in a 1.8 V, 0.25 /spl mu/m process.

De-embedding the noise figure of differential amplifiers

Abstract: Many radio-frequency circuits use differential topologies, whereas the instruments to evaluate them are inevitably single ended. Taking into account noise correlations, this work extends Friis' well-known equation for the noise figure of a cascade of two-ports to the case of three-ports, such as baluns, which surround a differential amplifier during measurements. The amplifier gain and noise figure may be accurately de-embedded with single-ended measurements on the cascade and on the baluns. The new formulas are experimentally validated.

A least-squares based method for autoregressive signals in the presence of noise

Abstract: The problem of estimating the unknown parameters of an autoregressive (AR) signal observed in white noise, including the signal power and the noise variance, is studied. A new type of least-squares method is developed which is based on a simple technique of estimating the observation noise variance by increasing the degree of the underlying AR model by one. The main feature of the presented method is that the consistent estimates of AR parameters can be directly achieved, with no need to prefilter noisy data or to make any parameter transformation.

Signal and noise separation: Art and science

Abstract: The separation of signal and noise is a central issue in seismic data processing. The noise is both random and coherent in nature, the coherent part often masquerading as signal. In this tutorial, we present some approaches to signal isolation, in which stacking is a central concept. Our methodology is to transform the data to a domain where noise and signal are separable, a goal that we attain by means of inversion. We illustrate our ideas with some of our favorite transformations: wavelets, eigenvectors, and Radon transforms. We end with the notion of risk, baseball, and the Stein estimator.

Speech intelligibility in noisy environments with one- and two-microphone hearing aids.

Abstract: In this study speech intelligibility in background noise was evaluated with 10 binaural hearing-aid users for hearing aids with one omnidirectional microphone and a hearing aid with a two-microphone configuration (enabling an omnidirectional as well as a directional mode). Signal-to-noise ratio (SNR) measurements were carried out for three different types of background noise (speech-weighted noise, traffic noise and restaurant noise) and two kinds of speech material (bisyllabic word lists and sentences). The average SNR improvement of the directional microphone configuration relative to the omnidirectional one was 3.4 dB for noise presented from 90 degrees azimuth. This improvement was independent of the specific type of noise and speech material, indicating that one speech-in-noise condition may yield enough relevant information in the evaluation of directional microphones and speech understanding in noise.

Visual signal detection with two-component noise: low-pass spectrum effects

Abstract: Detection of signals in natural images and scenes is limited by both noise and structure. The purpose of this study is to investigate phenomenological issues of signal detection in two-component noise. One component had a broadband (white) spectrum designed to simulate image noise. The other component was filtered to simulate two classes of low-pass background structure spectra: Gaussian-filtered noise and power-law noise. Measurements of human and model observer performance are reported for several aperiodic signals and both classes of background spectra. Human results are compared with two classes of observer models and are fitted very well by suboptimal prewhitening matched filter models. The nonprewhitening model with an eye filter does not agree with human results when background-noise-component power spectrum bandwidths are less than signal energy bandwidths.

Analysis of ground-bounce induced substrate noise coupling in a low resistive bulk epitaxial process: design strategies to minimize noise effects on a mixed-signal chip

Abstract: The industry trend toward system-on-chip solutions continues to push the limits of mixed-signal design. Increasing the integration of analog and digital circuitry causes a struggle to maintain analog signal integrity. Digital switching of noise coupling through the common substrate is both difficult to measure and difficult to control. This paper introduces and applies a practical first-order simulation methodology for performing a substrate noise analysis in a low resistive bulk process. Although this subject has been analyzed in numerous journal articles, few have applied their analysis method to a whole-chip design. This SPICE model will allow mixed-signal designers to determine design variables that will minimize substrate noise. This work elaborates on key aspects of substrate noise that available references do not handle adequately, including: sources of substrate noise, determination of power-rail and bulk-resonance frequencies, and alternatives for bulk biasing. The new model is used to analyze Motorola's 56824, the latest low-cost 16-bit digital signal processor design. The analysis includes the determination of: (1) the on-chip bus and I/O bus noise coupled to the substrate; (2) the dominant resonant frequencies in the chip; and (3) the best bulk-biasing alternative.

Inlet Noise Reduction by Shielding for the Blended-Wing-Body Airplane

Abstract: Noise shielding benefits associated with an advanced unconventional subsonic transport concept, the Blended-Wing-Body, were studied using a 4- percent scale, 3-engine nacelle model. The study was conducted in the Anechoic Noise Research Facility at NASA Langley Research Center. A high- frequency, wideband point source was placed inside the nacelles of the center engine and one of the side engines in order to simulate broadband engine noise. The sound field of the model was measured with a rotating microphone array that was moved to various stations along the model axis and with a fixed array of microphones that was erected behind the model. Ten rotating microphones were traversed a total of 22 degrees in 2-degree increments. Seven fixed microphones covered an arc that extended from a point in the exhaust exit plane of the center engine (and directly below its centerline) to a point 30 degrees above the jet centerline. While no attempt was made to simulate the noise emission characteristics of an aircraft engine, the model source was intended to radiate sound in a frequency range encompassing 1, 2, and 3 times the blade passage of a typical full-scale engine. In this study, the Blended-Wing-Body model was found to provide significant shielding of inlet noise. In particular, noise radiated downward into the forward sector was reduced by 20 to 25 dB overall in the full-scale frequencies from 2000 to 4000 Hz, decreasing to 10 dB or less at the lower frequencies. Also, it was observed that noise associated with the exhaust radiates into the sector directly below the model downstream to reduce shielding efficiency.

A method and system for updating noise estimates during pauses in an information signal

Abstract: The invention relates to an improved adaptive spectral estimator for estimating the spectral components in a signal (205) containing both an information signal, such as speech, and noise. A method and system provide for generating noise estimates (245) and then only updating the noise estimates during pauses in an information signal, when speech or other information is not detected, rather than continuously updating the noise estimates. A noise estimate is calculated for each frequency band and provides for the inclusion of a variable mathematical factor that can be set by the user to produce the best sound quality.