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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.
Statistical signal processing – analyzing and extracting information from signals and noise based on their stochastic properties; Linear time-invariant system theory, and transform theory; Polynomial signal processing – analysis of systems which relate input and output using polynomials; System identification [8] and classification ...
Pages in category "Statistical signal processing" The following 23 pages are in this category, out of 23 total. This list may not reflect recent changes. B.
William A Gardner (born Allen William Mclean, November 4, 1942) is a theoretically inclined electrical engineer who specializes in the advancement of the theory of statistical time-series analysis and statistical inference with emphasis on signal processing algorithm design and performance analysis. [1]
In stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical self-affinity of a signal. It is useful for analysing time series that appear to be long-memory processes (diverging correlation time, e.g. power-law decaying autocorrelation function) or 1/f noise.
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
Technical Program Chair: Louis L. Scharf 970 257 1981 30 March-1 April Atlanta, GA, USA General Chair: Ronald W. Schafer Technical Program Chair: Russell M. Mersereau 950 295 1982 3-5 May Paris, France General Chair: Claude Gueguen Technical Program Chair: Maurice Bellanger 1653 522 1983 14-16 April Boston, MA, USA
When a function () is a function of time and represents a physical signal, the transform has a standard interpretation as the frequency spectrum of the signal. The magnitude of the resulting complex-valued function S ( f ) {\displaystyle S(f)} at frequency f {\displaystyle f} represents the amplitude of a frequency component whose initial phase ...