Automatic Autocorrelation and Spectral Analysis

By:

Petrus M.T. Broersen

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Paperback / softback

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Description

"Automatic Autocorrelation and Spectral Analysis" gives random data a language to communicate the information they contain objectively. It takes advantage of greater computing power and robust algorithms to produce enough candidate models of a given group of data to be sure of providing a suitable one. Improved order selection guarantees that one of the best (often the best) will be selected automatically. Written for graduate signal processing students and for researchers and engineers using time series analysis for applications ranging from breakdown prevention in heavy machinery to measuring lung noise for medical diagnosis, this text offers: - tuition in how power spectral density and the autocorrelation function of stochastic data can be estimated and interpreted in time series models; - extensive support for the MATLAB® ARMAsel toolbox; - applications showing the methods in action; - appropriate mathematics for students to apply the methods with references for those who wish to develop them further.

Author Biography:

Piet M.T. Broersen received the Ph.D. degree in 1976, from the Delft University of Technology in the Netherlands. He is currently with the Department of Multi-scale Physics at TU Delft. His main research interest is in automatic identification on statistical grounds. He has developed a practical solution for the spectral and autocorrelation analysis of stochastic data by the automatic selection of a suitable order and type for a time series model of the data.

Release date Australia

October 13th, 2010

Author

Petrus M.T. Broersen

Audience

Professional & Vocational

Edition

Softcover reprint of hardcover 1st ed. 2006

Illustrations

104 Illustrations, black and white; XII, 298 p. 104 illus.

Pages

298

Dimensions

156x234x16

ISBN-13

9781849965811

Product ID

9985190

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