Automatic Autocorrelation and Spectral Analysis

Automatic Autocorrelation and Spectral Analysis

by Petrus M.T. Broersen


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Automatic Autocorrelation and Spectral Analysis by Petrus M.T. Broersen

Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.

Product Details

ISBN-13: 9781846283284
Publisher: Springer London
Publication date: 06/02/2006
Edition description: 2006
Pages: 298
Product dimensions: 6.10(w) x 9.25(h) x 0.36(d)

About the Author

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.

Table of Contents

Basic Concepts.- Periodogram and Lagged Product Autocorrelation.- ARMA Theory.- Relations for Time Series Models.- Estimation of Time Series Models.- AR Order Selection.- MA and ARMA Order Selection.- ARMASA Toolbox with Applications.- Advanced Topics in Time Series Estimation.

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