Statistical Methods in Control and Signal Processing, Vol. 103
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Overview
Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this work documents developments in statistical modelling, identification, estimation and signal processing. The book covers such topics as subspace methods, stochastic realization, state space modelling, and identification and parameter estimation.Synopsis
Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this work documents developments in statistical modelling, identification, estimation and signal processing. The book covers such topics as subspace methods, stochastic realization, state space modelling, and identification and parameter estimation.
Booknews
Summarizes the current state of certain areas in statistical and stochastic methods in control and signal processing, providing a sample of recent trends and the most representative results in stochastic modeling, identification, relative open problems, and applications. The section on modeling, identification, and estimation includes discussions of general-state space modeling, the multi-resolution approach to identifying system impulse response, and fuzzy random data obtained as vague perceptions of random phenomena. Signal processing is treated from such perspectives as the theory of cyclostationary processes and its applications, Bayesian approaches for robust array signal processing, and invariant features associated with a conditional distribution induced by self-similar patterns. Annotation c. by Book News, Inc., Portland, Or.