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Statistical signal processing is an approach which treats signals as stochastic processes, ... Spectral Analysis of Signals (PDF). NJ: Prentice Hall. Kay, Steven M ...
Kay, S. M. (1993). Fundamentals of Statistical Signal Processing: ... Mathematical Methods and Algorithms for Signal Processing. Prentice-Hall. ISBN ...
The following terms are used by electrical engineers in statistical signal processing studies ... S.M. Kay, Fundamentals of Statistical Signal ... of statistical ...
In statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density (also known as the power spectral density) of a signal from a sequence of time samples of the signal. [1] Intuitively speaking, the spectral density characterizes the frequency content of
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In many practical signal processing problems, the objective is to estimate from measurements a set of constant parameters upon which the received signals depend. There have been several approaches to such problems including the so-called maximum likelihood (ML) method of Capon (1969) and Burg's maximum entropy (ME) method.
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other. [1]
In signal processing, white noise is a random signal having equal intensity at different frequencies, giving it a constant power spectral density. [1] The term is used with this or similar meanings in many scientific and technical disciplines, including physics, acoustical engineering, telecommunications, and statistical forecasting. White ...