Spectrum Analysis

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Fundamentals of Spectrum Analysis

Author	: Christoph Rauscher
Publisher	:
Total Pages	: 219
Release	: 2007
ISBN-10	: 3939837016
ISBN-13	: 9783939837015
Rating	: 4/5 (015 Downloads)

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Book Synopsis Fundamentals of Spectrum Analysis by : Christoph Rauscher

Download or read book Fundamentals of Spectrum Analysis written by Christoph Rauscher and published by . This book was released on 2007 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fundamentals of Spectrum Analysis Related Books

Language: en
Pages: 219

Fundamentals of Spectrum Analysis

Authors: Christoph Rauscher

Categories: Spectrum analyzers

Type: BOOK - Published: 2007 - Publisher:

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Language: en
Pages: 108

Spectral Analysis of Signals

Authors: Yanwei Wang

Categories: Computers

Type: BOOK - Published: 2005 - Publisher: Morgan & Claypool Publishers

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Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar

Language: en
Pages: 210

Bayesian Spectrum Analysis and Parameter Estimation

Authors: G. Larry Bretthorst

Categories: Mathematics

Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media

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This work is essentially an extensive revision of my Ph.D. dissertation, [1J. It 1S primarily a research document on the application of probability theory to th

Language: en
Pages: 126

Singular Spectrum Analysis for Time Series

Authors: Nina Golyandina

Categories: Mathematics

Type: BOOK - Published: 2013-01-19 - Publisher: Springer Science & Business Media

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Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate stati

Language: en
Pages: 167

Singular Spectrum Analysis

Authors: J.B. Elsner

Categories: Business & Economics

Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media

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The term singular spectrum comes from the spectral (eigenvalue) decomposition of a matrix A into its set (spectrum) of eigenvalues. These eigenvalues, A, are th