White noise

About: White noise is a research topic. Over the lifetime, 16496 publications have been published within this topic receiving 318633 citations.

Transient and convergent behavior of the adaptive line enhancer

Abstract: The adaptive line enhancer (ALE) was first described as a practical technique for separating the periodic from the broad-band components of an input signal and for detecting the presence of a sinusoid in white noise. Subsequent work has shown that this adaptive filtering structure is applicable to spectral estimation, predictive deconvolution, speech processing, interference rejection, and other applications which have historically used matrix inversion or Levinson's algorithm techniques. This paper uses an eigenvalue-eigenvector analysis of the expected ALE impulse response vector to demonstrate properties of the convergent filter and to quantify the convergence time and characteristics of the ALE. In particular the ALE's response to a sinusoid plus white noise input is derived and compared to a computer simulation of the ALE with such an input. The eigenvalue-eigenvector technique is then used to evaluate the ALE's performance as an adaptive prewhitener for autoregressive (AR) models with white observation noise. A method is demonstrated which prevents the problem of spectral estimation bias which usually accrues from the observation noise.

Further results in the fast estimation of a single frequency

Abstract: The author proposes a new frequency estimator for a single complex sinusoid in complex white Gaussian noise. The estimator is applicable to problems in communications requiring high speed, recursive frequency estimation. The estimator is computationally efficient yet obtains near optimum performance at moderate signal-to-noise ratios. >

A parametric formulation of the generalized spectral subtraction method

Abstract: In this paper, two short-time spectral amplitude estimators of the speech signal are derived based on a parametric formulation of the original generalized spectral subtraction method. The objective is to improve the noise suppression performance of the original method while maintaining its computational simplicity. The proposed parametric formulation describes the original method and several of its modifications. Based on the formulation, the speech spectral amplitude estimator is derived and optimized by minimizing the mean-square error (MSE) of the speech spectrum. With a constraint imposed on the parameters inherent in the formulation, a second estimator is also derived and optimized. The two estimators are different from those derived in most modified spectral subtraction methods, which are predominantly nonstatistical. When tested under stationary white Gaussian noise and semistationary Jeep noise, they showed improved noise suppression results.

Temporal properties of the visual detectability of moving spatial white noise.

Abstract: We obtained movement detection thresholds for two-dimensional random speck-patterns ("Julesz" patterns) homogeneously moving over the whole target field (5.21 x 5.31 degrees of visual angle). We alternated between two uncorrelated but otherwise similar patterns, one moving with velocity leads to V1, the other with velocity leads to V2, such that each pattern was on for T ms. We masked this pattern (signal) with spatio-temporal white noise ("snow"). The total r.m.s. contrast was kept constant, whereas the ration of the r.m.s. contrasts of signal and noise was varied. The square of this ratio was designated SNR. At low SNR values the pattern was not perceptually different from the snow alone. At high SNR values the subject detected spatio-temporal correlation (e.g., movement). In these experiments we determined the threshold SNR values as a measure of the detectability of spatio-temporal correlation as a function of the parameters T, leads to V1, and leads to V2. When leads to V1 and leads to V2 were sufficiently dissimilar one of three percepts occurred: for very large T the alternation could be followed, for very small T two transparent, simultaneously moving sheets of noise-pattern with different velocities could be seen. For intermediate T-values no systematic movement at all could be observed. At these T-values the threshold SNR was maximal. This "'critical" T-value decreased with increasing velocity. We found that it was possible to have more than one percept of uniform smooth movement at a single location in the visual field if these movements had velocity vectors with an angular difference of at least 30 deg or if their magnitudes differed by at least a factor of 4.