Automatic Autocorrelation and Spectral Analysis

Gebundene Ausgabe
(298 Seiten)
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ISBN-13:
9781846283284
Einband:
Gebundene Ausgabe
Erscheinungsdatum:
20.04.2006
Seiten:
298
Autor:
Petrus M.T. Broersen
Gewicht:
581 g
SKU:
INF3002380908
Sprache:
Englisch
Beschreibung:

This book describes a method which fulfils 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.
Shows the reader which spectral methods (algorithms) are useful in practice
Introduction.- 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. ARMASA Toolbox.
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.

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