White noise

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

Measurements of the binaural temporal window using a detection task

Abstract: Two experiments investigated the shape of the binaural temporal window using a detection task. In experiment 1, a 10-ms tone burst was presented binaurally out-of-phase during a burst of white noise, which changed from being interaurally uncorrelated, to correlated, and back to uncorrelated. The tone occurred during the correlated portion of the noise in one interval of each 2I-FC trial. Detection thresholds were recorded using a 2-down/1-up adaptive procedure. Thresholds were measured for different durations of correlated noise (0–960 ms), frequencies of tone burst (125, 250, 500, and 1000 Hz) and levels of noise [20, 30, 40, and 50 dB(SPL)/Hz]. Window shapes based on nine candidate functions were fitted to the data using the assumption that the binaural masking release was related to the overall interaural correlation of noise admitted by the window. Fitted windows included both a forward and a backward lobe. Gaussian functions tended to give closer fits than exponential and rounded-exponential functions, and simple functions gave more parsimonious fits that those which included dynamic-range-limiting terms. Using simple Gaussian fits, the shape of the window was largely independent of frequency and level, and the windows for individual listeners had equivalent rectangular durations ranging from 55 to 188 ms. The asymmetry was variable, although forward lobes were generally shorter than backward lobes. Experiment 2 ruled out the possibility that the forward lobe might be an artefact caused by distraction of the listener, when the interaural phase change in the noise closely followed the signal. In this experiment, the out-of-phase tone was presented during a burst of partially correlated noise which changed, after a variable interval, to a fully correlated noise. Thresholds for detecting the tone rose (i.e., performance worsened) as the interval was increased. Distraction would have produced the opposite effect.

Optimum Signal-Processing for Pulse-Amplitude Spectrometry in the Presence of High-Rate Effects and Noise

Abstract: In this paper the idea of a general signal processing system which should satisfy various pulse rate and noise requirements is explored. Optimum processing functions (weighting functions) are considered for an ideal system, and for real conditions where effects like imperfect pole-zero cancellation are present. Time-variant filters of the gain-varying class are used to realize the required optimum weighting functions of finite width. It is shown how nonfinite-width weighting functions of some time-invariant filters can be modified into finite-width functions by switching. These switched-gain time-variant filters are somewhat limited in choice of weighting functions. A general processing system can be realized employing filters with continuously time-variant elements. In particular, a gain-varying element (i.e., an analog multiplier) can be used in conjunction with an integrator to realize arbitrary weighting functions, and therefore the theoretically maximum signal-to-noise ratio. The system is time-variant only for the noise and not for the signal, so that it does not require high precision of the time-variant element. The system output is independent of the gating interval, and does not require precise timing. A method for evaluation of such systems in terms of noise, ballistic deficit and sensitivity to parameter variations is given.

Modeling Multiscale Subbands of Photographic Images with Fields of Gaussian Scale Mixtures

Abstract: The local statistical properties of photographic images, when represented in a multi-scale basis, have been described using Gaussian scale mixtures. Here, we use this local description as a substrate for constructing a global field of Gaussian scale mixtures (FoGSM). Specifically, we model multi-scale subbands as a product of an exponentiated homogeneous Gaussian Markov random field (hGMRF) and a second independent hGMRF. We show that parameter estimation for this model is feasible, and that samples drawn from a FoGSM model have marginal and joint statistics similar to subband coefficients of photographic images. We develop an algorithm for removing additive Gaussian white noise based on the FoGSM model, and demonstrate denoising performance comparable with state-of-the-art methods.

Analysis of Online Secondary-Path Modeling With Auxiliary Noise Scaled by Residual Noise Signal

Abstract: Online secondary-path modeling of active noise control (ANC) systems may be effectively implemented by injecting an auxiliary white noise whose magnitude is scaled by a function of residual noise signal. In this paper, a filtered-X LMS (FXLMS) based narrowband ANC system is analyzed, whose online secondary-path modeling is based on the use of an auxiliary white noise scaled by one-sample-delayed residual noise signal. Difference equations governing the dynamics of the entire system and closed-form expressions for steady-state mean-square errors (MSE) as well as the residual noise power are derived and discussed in detail. Extensive simulations are conducted to confirm the validity of the analytical findings.