Showing papers on "Noise measurement published in 1995"

A signal subspace approach for speech enhancement

Abstract: A comprehensive approach for nonparametric speech enhancement is developed. The underlying principle is to decompose the vector space of the noisy signal into a signal-plus-noise subspace and a noise subspace. Enhancement is performed by removing the noise subspace and estimating the clean signal from the remaining signal subspace. The decomposition can theoretically be performed by applying the Karhunen-Loeve transform (KLT) to the noisy signal. Linear estimation of the clean signal is performed using two perceptually meaningful estimation criteria. First, signal distortion is minimized while the residual noise energy is maintained below some given threshold. This criterion results in a Wiener filter with adjustable input noise level. Second, signal distortion is minimized for a fixed spectrum of the residual noise. This criterion enables masking of the residual noise by the speech signal. It results in a filter whose structure is similar to that obtained in the first case, except that now the gain function which modifies the KLT coefficients is solely dependent on the desired spectrum of the residual noise. The popular spectral subtraction speech enhancement approach is shown to be a particular case of the proposed approach. It is proven to be a signal subspace approach which is optimal in an asymptotic (large sample) linear minimum mean square error sense, assuming the signal and noise are stationary. Our listening tests indicate that 14 out of 16 listeners strongly preferred the proposed approach over the spectral subtraction approach. >

Noise estimation techniques for robust speech recognition

Abstract: Two new techniques are presented to estimate the noise spectra or the noise characteristics for noisy speech signals No explicit speech pause detection is required Past noisy segments of just about 400 ms duration are needed for the estimation Thus the algorithm is able to quickly adapt to slowly varying noise levels or slowly changing noise spectra This techniques can be combined with a nonlinear spectral subtraction scheme The ability can be shown to enhance noisy speech and to improve the performance of speech recognition systems Another application is the realization of a robust voice activity detection

Applications of cumulants to array processing .I. Aperture extension and array calibration

Abstract: An interpretation for the use of cumulants in narrowband array processing problems is proposed. It is shown how fourth-order cumulants of multichannel observations increase the directional information compared with second-order statistics. Based on the interpretation, it is shown how cumulants can be used to increase the effective aperture of an arbitrary antenna array. The amount of partial information necessary to jointly calibrate an arbitrary array and estimate the directions of far-field sources is also investigated. It is proven that the presence of a doublet and use of fourth-order cumulants is sufficient to accomplish this task. The proposed approach is computationally efficient and more general than covariance-based algorithms that have addressed the calibration problem under constraints. A class of beamforming techniques is proposed to recover the source waveforms. Proposed estimation procedures are based on cumulants, which bring insensitivity to the spatial correlation structure of additive Gaussian measurement noise. Simulations are provided to illustrate the use of the proposed algorithms. >

Signal separation by symmetric adaptive decorrelation: stability, convergence, and uniqueness

Abstract: The performance of signal enhancement systems based on adaptive filtering is highly dependent on the quality of the noise reference. In the LMS algorithm, signal leakage into the noise reference leads to signal distortion and poor noise cancellation. The origin of the problem lies in the fact that LMS decorrelates the signal estimate with the noise reference, which, in the case of signal leakage, makes little sense. An algorithm is proposed that decorrelates the signal estimate with a "signal-free" noise estimate, obtained by adding a symmetric filter to the classical structure. The symmetric adaptive decorrelation (SAD) algorithm no longer makes a distinction between signal and noise and is therefore a signal separator rather than a noise canceler. Stability and convergence are of the utmost importance in adaptive algorithms and hence are carefully studied. Apart from limitations on the adaptation constants, stability around the desired solution can only be guaranteed for a subclass of signal mixtures. Furthermore, the decorrelation criterion does not yield a unique solution, and expressions for the "phantom" solutions are derived. Simulations with short FIR filters confirm the predicted behavior. >

Conversion gain and noise of niobium superconducting hot-electron-mixers

Abstract: A study has been done of microwave mixing at 20 GHz using the nonlinear (power dependent) resistance of thin niobium strips in the resistive state. Our experiments give evidence that electron-heating is the main cause of the nonlinear phenomenon. Also a detailed phenomenological theory for the determination of conversion properties is presented. This theory is capable of predicting the frequency-conversion loss rather accurately for arbitrary bias by examining the I-V characteristic, Knowing the electron temperature relaxation time, and using parameters derived from the I-V-characteristic also allows us to predict the -3-dB IF bandwidth. Experimental results are in excellent agreement with the theoretical predictions. The requirements on the mode of operation and on the film parameters for minimizing the conversion loss (and even achieving conversion gain) are discussed in some detail. Our measurements demonstrate an intrinsic conversion loss as low as 1 dB. The maximum IF frequency defined for 3-dB drop in conversion gain, is about 80 MHz. Noise measurements indicate a device output noise temperature of about 50 K and SSB mixer noise temperature below 250 K. This type of mixer is considered very promising for use in low-noise heterodyne receivers at THz frequencies. >

Noise Theory of Linear and Nonlinear Circuits

Abstract: LINEAR SYSTEMS. Some Milestones in the Development of Noise Theory. Noise in One--Ports. Noise Characteristics of Multi--Ports. Noise Parameters. Noise Measure and Graphic Representations. Noise of Embedded Networks. NON--LINEAR SYSTEMS. Noise in Non--Linear Systems: Theory. Noise in Non--Linear Systems: Examples and Conclusion. Multi--Port Volterra Transfer Functions. Appendices.

Performance analysis of QAM systems under class A impulsive noise environment

Abstract: This paper describes the performance of QAM (quadrature amplitude modulation) systems under impulsive noise environment. In the analysis, we employ, as a model of the impulsive noise, Middleton's (1977) model labeled class A. First, the statistical characteristics of the in-phase and quadrature components of the impulsive noise are investigated, and it is proved that, in contrast to Gaussian noise, these components are dependent especially for the impulsive noise with small impulsive indices. Next, with consideration of the dependence between the in-phase and quadrature components of the noise, the performance of QAM systems with the conventional receiver designed for Gaussian noise is analyzed. The numerical results show that the performance is much worse than that achieved under Gaussian noise. Moreover, we show the design of the maximum likelihood receiver for class A impulsive noise and the great performance improvement by this receiver is confirmed. >

Voice activity detection driven noise remediator

Abstract: A method and apparatus for improving sound quality in a digital cellular radio system receiver. A voice activity detector uses an energy estimate to detect the presence of speech in a received speech signal in a noise environment. When no speech is present the system attenuates the signal and inserts low pass filtered white noise. In addition, a set of high pass filters are used to filter the signal based upon the background noise level. This high pass filtering is applied to the signal regardless of whether speech is present. Thus, a combination of signal attenuation with insertion of low pass filtered white noise during periods of non-speech, along with high pass filtering of the signal, improves sound quality when decoding speech which has been encoded in a noisy environment.

Adaptive filtering of stable processes for active attenuation of impulsive noise

Abstract: Describes a new class of algorithms for active noise control (ANC) for use in environments in which impulsive noise is present. The well known filtered-X and filtered-U ANC algorithms are designed to minimize the variance of a measured error signal. For impulsive noise, which can be modeled using non-Gaussian stable processes, these standard approaches are not appropriate since the second order moments do not exist. The authors propose a new class of adaptive algorithms for ANC that are based on the minimization of a fractional lower order moment, p<2. By studying the effect of p on the convergence behavior of adaptive algorithms, they observe that superior performance is obtained by choosing p/spl ap//spl alpha/ where /spl alpha/<2 is a parameter reflecting the degree of impulsiveness of the noise. Applications of this approach to noise cancellation in a duct are presented.

Development and analysis of an adaptive noise equalizer

Abstract: The paper presents the development and analysis of a narrowband adaptive noise equalizer (ANE), which can either amplify or attenuate narrowband noise. The output of the ANE system contains residual narrowband components, the amplitudes of which can be linearly and arbitrarily controlled by adjusting the gain parameter of the equalizer, thus providing the desired noise shaping capability. The characteristics of the ANE system are analyzed and applied to active noise control. >

A Bayesian approach to the restoration of degraded audio signals

Abstract: In this paper we derive the a posteriori probability for the location of bursts of noise additively superimposed on a Gaussian AR process. The theory is developed to give a sequentially based restoration algorithm suitable for real-time applications. The algorithm is particularly appropriate for digital audio restoration, where clicks and scratches may be modelled as additive bursts of noise. Experiments are carried out on both real audio data and synthetic AR processes and significant improvements are demonstrated over existing restoration techniques. >

Noise estimating system for use with audio reproduction equipment

Abstract: The disclosed system for estimating the ambient noise level in a listening space includes a memory for storing a plurality of noise values at memory locations therein, each of the noise values being representative of the ambient noise in the listening space associated with a corresponding set of conditions of the listening space. The system further includes an address generator for generating an address signal in response to a current set of conditions of the listening space so that the address signal accesses a location of the memory storing the noise value associated with the current set of conditions. The system further includes a noise signal generator for generating a noise signal in response to the address signal, the noise signal corresponding to the noise value associated with the current set of conditions so that the noise signal is representative of the ambient noise level.

Characterisation and modelling of artificial light interference in optical wireless communication systems

Abstract: Wireless indoor infrared transmission systems are affected by noise and interference induced by natural and artificial ambient light. While the shot noise induced on the receiver photodiode by steady ambient light has been extensively described and included in system models, the interference produced by artificial light has only been mentioned as a source of degradation and quite simple descriptions have been presented. This paper presents a characterisation (through extensive measurements) of the interference produced by artificial light and proposes a simple model to describe it. These measurements show that artificial light can introduce significant in-band components for systems operating at bit rates up to several Mbit/s. Therefore it is essential to include it as part of the optical wireless indoor channel. The measurements show that fluorescent lamps driven by solid state ballasts produce the wider band interfering signals, and are then expected to be the more important source of degradation in optical wireless systems.

A new self-tuning algorithm for the frequency estimation of distorted signals

Abstract: This paper introduces a new self-tuning digital signal processing algorithm for local power system frequency deviation measurement. The algorithm is derived using the nonrecursive least error square technique accompanied with an updating procedure, which generally improves the algorithm properties: the measurement range; the immunity to a random noise; and the accuracy. The algorithm developed takes into account the components of the fundamental frequency, the second through the M-th harmonics and a decaying DC component, so it could be used for the real-time distorted signals frequency estimation as well as for the harmonics measurement. To demonstrate the efficiency of the algorithm proposed, the results of the computer simulated, experimentally obtained and real-life data records tests are presented. >

Noise in chaotic data: Diagnosis and treatment

Abstract: A prominent limiting factor in the analysis of chaotic time series are measurement errors in the data. We show that this influence can be quite severe, depending on the nature of the noise, the complexity of the signal, and on the application one has in mind. Theoretical considerations yield general upper bounds on the tolerable noise level for dimension, entropy and Lyapunov estimates. We discuss methods to detect and analyze the noise present in a measured data set. We show how the situation can be improved by nonlinear noise reduction. (c) 1995 American Institute of Physics.

Telecommunications speech signal improvement by reduction of residual noise

Abstract: A telecommunications network service overcomes the annoying effects of transmitted noise by signal processing which filters out the noise using a model-based iterative signal estimator. The estimator is provided with a current estimate of the noise power spectral density, using signal frame samples determined by a voice activity detector to be noise-only frames. The signal estimator makes intra-frame iterations of the current frame while using smoothing across LSP parameters of adjacent frames, recent past frames, and up to two contiguous future frames. Non-stationary noise created by the iterative filtering is further reduced in one or more post-filtering stages that use knowledge of the nature of the low level non-stationary noise events.

Fundamental noise limits for miniature acoustic and vibration sensors

Abstract: Recent technological advances in microfabrication and fiber optics have made practical the construction of very small, sensitive sensors for acoustic or vibration measurements. As the sensitivity is increased or the size is decreased, a sensor becomes more susceptible to mechanical noise resulting from molecular agitation. Traditional noise analysis is often focused exclusively on electrical or optical noise ; consequently, mechanical-thermal noise may not be considered in new types of sensors until the prototype testing reveals an unexpectedly high noise floor. Fortunately, mechanical-thermal noise is relatively easy to estimate early in the design process because the equivalent noise force is only a function of the temperature and the mechanical losses in the sensor. There are a number of specific techniques that are applicable for evaluating either the total mechanical-thermal noise or the spectral distribution of that noise for simple or complex sensors. These techniques are presented and, in addition, a summary of other noise components is given in the context of design guidelines for high-sensitivity sensors.

Method for attenuating coherent noise in marine seismic data

Abstract: A method for adaptively creating a filter for removing coherent environmental noise from a multitrace digitized seismic recording requires the presence, on the recording, of a limited sample of pure noise that is uncontaminated by desired signal. The pure noise sample is used to discover the location of the noise source and from that discovery, to extrapolate and reconstruct the characteristics of the noise envelope as it would appear on the seismic recording. The reconstructed noise envelope is used as a noise reference for input to a conventional iterative adaptive noise cancellation filter loop. For stability, the loop gain is minimized by temporally and spatially averaging the filter coefficients for each sample interval.

Multiparameter optimization of inverse filtering algorithms

Abstract: This paper investigates inverse filtering of transient signals. The problem is ill-conditioned, which means that a small uncertainty in the measurement causes large deviations in the reconstructed signal. This amplified noise has to be suppressed at the price of bias in the estimation. The most difficult task is to find the optimal degree of noise reduction. Deconvolution algorithms are usually controlled by one or a few parameters. Several algorithms can be found in the literature to find the best setting of inverse filtering methods; however, usually methods with only one free parameter are handled. In this paper, an algorithm is proposed to optimize several parameters, on the basis of a spectral model. Multiparameter inverse filtering methods have the advantage that they can be better adapted to the measurement system, and to the noise and signal to be measured. The superiority of the proposed optimization method is demonstrated both on simulated and on experimental data.

A maximum likelihood procedure for a universal adaptation method based on HMM composition

Abstract: This paper proposes an adaptation method for universal noise (additive noise and multiplicative distortion) based on the HMM composition (compensation) technique. Although the original HMM composition can be applied only to additive noise, our new method can estimate multiplicative distortion by maximizing the likelihood value. The signal-to-noise ratio is automatically estimated as part of the estimation of multiplicative distortion. Phoneme recognition experiments show that this method improves recognition accuracy for noisy and distorted speech.

Optimum distortion-invariant filter for detecting a noisy distorted target in nonoverlapping background noise

Abstract: An optimal distortion-invariant filter for detecting a distorted target in input noise is designed. The input noise consists of two kinds of noise, overlapping additive noise and nonoverlapping background noise. We obtain the filter function by statistically maximizing the peak-to-output-energy ratio criterion, which is defined as the ratio of the square of the expected value of the output signal at the target location to the expected value of the average output energy. This results in a filter output with a well-defined output peak at the target location and a low output-noise floor. This filter is designed to take into account the effects of both overlapping additive noise and nonoverlapping background noise, the finite size of the input data, and the target distortion. The special cases of detecting a distorted target in nonoverlapping background noise and detecting a distorted target in overlapping additive noise are discussed. Computer simulation results are provided to show the performance of the filter.

Use of noise segmentation for noise cancellation

Abstract: What is disclosed is a method and system for improving noise cancellation in a signal containing speech by classifying noise frames by their characteristics, and estimating noise based on only one classification at a time. In some instances, the disclosed method further directs the noise estimator and noise canceller to utilize only a designated noise class. Also, the disclosed system can automatically switch between pre-processing and post-processing modes in response to detected changes in acoustic environments.

Transformer tap position estimation and bad data detection using dynamic signal modelling

Abstract: Tracking estimation of a transformer tap position is considered. An estimation algorithm incorporating additional information about the dynamic behaviour of the measurements and tap positions is developed. It is based on the simultaneous state and tap position estimation method augmented by measurement prefiltering based bad data detection and incorporation of a tap position dynamics model into the estimation algorithm. Increased bad data identification reliability and the robustness of the estimates to the measurement noise is obtained. The performance of the algorithm has been examined using the IEEE 30 and 118-node systems. >

Improved multimode fibre link BER calculations due to modal noise and non-self-pulsating laser diodes

Abstract: A modal noise model is presented that combines many features of previous theories such as varying fibre contrast, exponential noise p.d.f. and Gaussian noise p.d.f. The model also includes a new feature: the ability to treat multiple lossy connectors in the same link. This model is verified through extensive experimentation and is shown to be conservative, i.e. predicted noise penalties are larger than those observed. Using the model, modal noise penalties are predicted for a number of different link configurations, and laser parameters that result in acceptable amounts of modal noise are identified. The model is also demonstrated as a design tool for determining laser parameters that result in acceptable amounts of modal noise in typical links.

Applications of cumulants to array processing. II. Non-Gaussian noise suppression

Abstract: The main motivation of using higher order statistics in signal processing applications has been their insensitivity to additive colored Gaussian noise. The main objection to those methods is their possible vulnerability to non-Gaussian noise. The authors investigate the effects of non-Gaussian ambient noise on cumulant-based direction-finding systems using the interpretation for the information provided by cumulants for array processing applications described in Dogan and Mendek. they first demonstrate the suppression of uncorrelated non-Gaussian noise that has spatially varying statistics. Then, they indicate methods to suppress spatially colored non-Gaussian noise using cumulants and an additional sensor whose measurement noise component is independent of the noise components of the original array measurements. They also indicate the noise suppression properties of the virtual-ESPRIT algorithm proposed in Dogan and Mendel. In addition, they propose a method that combines second- and fourth-order statistics together in order to suppress spatially colored non-Gaussian noise. Finally, they also illustrate how to suppress spatially colored non-Gaussian noise when the additional sensor measurement is not available. Simulations are presented to verify the results. >

Likelihood ratio partitions for distributed signal detection in correlated Gaussian noise

Abstract: A distributed detection system is considered in which two sensors and a fusion center jointly process the output of a random data source. It is assumed that the null and alternative distributions are spatially correlated Gaussian, differing in the mean; thus the random source is either noise only or a deterministic signal plus noise. The authors characterize noise models for which the optimal system employs marginal likelihood ratio tests. In the setup where each sensor draws one local observation, we succeed in obtaining a sufficient condition on the noise mean and covariance under which the optimal binary quantizers are contiguous partitions of the marginal observation space.

Optimizing speech enhancement by exploiting masking properties of the human ear

Abstract: The problem of speech enhancement and mainly noise reduction in speech remains a key-point of hand-free telecommunications. A great number of techniques have been already put forward and for a few years an auditory model has been investigated in noise reduction. A new approach for enhancing a speech signal degraded by uncorrelated stationary additive noise is developed. In this approach the simultaneous masking effect of the human ear is exploited. Two states "noise masked/noise unmasked" are derived from a noise masking threshold computed using a rough estimate of the speech signal. Then a speech signal estimator is proposed as a weighted sum of the individual estimators in each state. The gain in the signal to noise ratio (SNR) and a distortion measure indicate some improvement in real noise conditions. Subjectively this improvement is noticeable only at high input SNRs.

An experimental mm-wave receiver system for measuring phase noise due to atmospheric turbulence

Abstract: The ultimate limitation of phase coherence in one-way communication systems is due to the irreducible propagation phase noise impressed upon a carrier wave due to scattering by atmospheric turbulence. The paper describes an experimental receiver designed to measure that phase noise using, initially, a satellite down link path and the 40 GHz propagation beacon of ITALSAT. Particular features of the system include: extremely low phase noise of the microwave first boal oscillator, complex demodulation (I & Q) without carrier phase acquisition (i.e. "on the fly") and menu driven interface electronics and data handling by a laptop acting as data logger and controller/house keeper of the system. The main design parameters are presented and include the various theoretical and experimental Lc(f) (dBc/Hz).

Pre-emphasis and speech recognition

Abstract: It is known that noise can significantly decrease the performance of a speech recognition system. To solve this problem, many speech processing algorithms have been developed. Most of them assume that the noise level is constant, or is to be evaluated in the course of the algorithm. The paper addresses a particular kind of noise: the type introduced by pre-emphasis of the speech signal. A new enhancement speech procedure is presented which allows a more relevant spectrum without the need for an a priori knowledge of the noise intensity. It is shown that this approach can greatly increase the recognition rate.