Topic
White noise
About: White noise is a research topic. Over the lifetime, 16496 publications have been published within this topic receiving 318633 citations.
Papers published on a yearly basis
Papers
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TL;DR: It is shown that the classical prediction problem must be reformulated when the relation function is taken into consideration, and this leads to a new perspective concerning the concept of complex white noise as well as the modeling of any signal as the output of a linear system driven by a white noise.
Abstract: The second-order statistical properties of complex signals are usually characterized by the covariance function. However, this is not sufficient for a complete second-order description, and it is necessary to introduce another moment called the relation function. Its properties, and especially the conditions that it must satisfy, are analyzed both for stationary and nonstationary signals. This leads to a new perspective concerning the concept of complex white noise as well as the modeling of any signal as the output of a linear system driven by a white noise. Finally, this is applied to complex autoregressive signals, and it is shown that the classical prediction problem must be reformulated when the relation function is taken into consideration.
256 citations
TL;DR: It is shown that for small changes around the optimum solution, the proposed update algorithm approximates the Gauss-Newton update without requiring a matrix inversion, and the transient response is approximately independent of the number of sinusoids or their power levels.
Abstract: A constrained adaptive infinite-impulse-response (IIR) filter consisting of a cascade of biquadratic notch sections is used to track multiple sinusoids. The structure can be used to isolate individual sinusoids. It is shown that for small changes around the optimum solution, the proposed update algorithm approximates the Gauss-Newton update without requiring a matrix inversion. Furthermore, the transient response is approximately independent of the number of sinusoids or their power levels. Important adaptive line enhancement performance criteria, such as signal-to-noise improvement ratio and the bias in the frequency estimate assuming white noise, are derived for the single-sinusoid case. Computer simulations are used to demonstrate the performance of the notch filter under a wide range of conditions. >
256 citations
TL;DR: Simulation results on both white noise and 1/f noise show that the CMSE provides higher entropy reliablity than the MSE approach for large time scale factors, and experimental results demonstrate that the proposed CMSE-based feature extractor provides higher separability than the LSTM-basedfeature extractor.
Abstract: Multiscale entropy (MSE) was recently developed to evaluate the complexity of time series over different time scales. Although the MSE algorithm has been successfully applied in a number of different fields, it encounters a problem in that the statistical reliability of the sample entropy (SampEn) of a coarse-grained series is reduced as a time scale factor is increased. Therefore, in this paper, the concept of a composite multiscale entropy (CMSE) is introduced to overcome this difficulty. Simulation results on both white noise and 1/f noise show that the CMSE provides higher entropy reliablity than the MSE approach for large time scale factors. On real data analysis, both the MSE and CMSE are applied to extract features from fault bearing vibration signals. Experimental results demonstrate that the proposed CMSE-based feature extractor provides higher separability than the MSE-based feature extractor.
256 citations
TL;DR: In this paper, an analytical study of the failure region of the first excursion reliability problem for linear dynamical systems subjected to Gaussian white noise excitation is carried out with a view to constructing a suitable importance sampling density for computing the failure probability.
255 citations