Statistical Signal Processing

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März 2002



Modern information systems must handle huge amounts of data having variednatural or technological origins. Automated processing of these increasingsignal loads requires the training of specialists capable of formalisingthe problems encountered.This book supplies a formalised, concise presentation of the basis ofstatistical signal processing. Equal emphasis is placed on approachesrelated to signal modelling and to signal estimation. In order to supplythe reader with the desirable theoretical fundamentals and to allow him tomake progress in the discipline, the results presented here are carefullyjustified.The representation of random signals in the Fourier domain and theirfiltering are considered. These tools enable linear prediction theory andrelated classical filtering techniques to be addressed in a simple way.The spectrum identification problem is presented as a first step towardspectrum estimation, which is studied in non-parametric and parametricframeworks.The later chapters introduce synthetically further advanced techniquesthat will enable the reader to solve signal processing problems of ageneral nature.Rather than supplying an exhaustive description of existing techniques,this book is designed for students, scientists and research engineersinterested in statistical signal processing and who need to acquire thenecessary grounding to address the specific problems with which they maybe faced. It also supplies a well-organized introduction to theliterature.The CD-ROM contains MATLAB programs in HTML format and is intended toprovide simulation examples (program listings + simulation results) Inaddition, it also presents some basics of probability.


1. Introduction.- 2. Random Processes.- 3. Power Spectrum of WSS Processes.- 4. Spectral Representation of WSS Processes.- 5. Filtering of WSS Processes.- 6. Important Particular Processes.- 7. Non-linear Transforms of Processes.- 8. Linear Prediction of WSS Processes.- 9. Particular Filtering Techniques.- 10. Rational Spectral Densities.- 11. Spectral Identification of WSS Processes.- 12. Non-parametric Spectral Estimation.- 13. Parametric Spectral Estimation.- 14. Higher Order Statistics.- 15. Bayesian Methods and Simulation Techniques.- 16. Adaptive Estimation.- A. Elements of Measure Theory.- C. Extension of a Linear Operator.- D. Kolmogorov's Isomorphism and Spectral Representation...- E. Wold's Decomposition.- F. Dirichlet's Criterion.- G. Viterbi Algorithm.- H. Minimum-phase Spectral Factorisation of Rational.- I. Compatibility of a Given Data Set with an Autocovariance Set.- 1.1 Elements of Convex Analysis.- 1.2 A Necessary and Sufficient Condition.- J. Levinson's Algorithm.- K. Maximum Principle.- L. One Step Extension of an Autocovariance Sequence.- N. General Solution to the Trigonometric Moment Problem ..- O. A Central Limit Theorem for the Empirical Mean.- P. Covariance of the Empirical Autocovariance Coefficients ...- Q. A Central Limit Theorem for Empirical Autocovariances ..- R. Distribution of the Periodogram for a White Noise.- S. Periodogram of a Linear Process.- T. Variance of the Periodogram.- U. A Strong Law of Large Numbers (I).- V. A Strong Law of Large Numbers (II).- W. Phase-amplitude Relationship for Minimum-phase Causal Filters.- X. Convergence of the Metropolis-Hastings Algorithm.- Y. Convergence of the Gibbs Algorithm.- Z. Asymptotic Variance of the LMS Algorithm.- References.


From the reviews:"This book is a formal introduction to signal image processing, and a rather complete one too. ... a good reference book to have if you are a research student, a practitioner interested in fundamentals of signal processing and their implementation, a teacher of signal processing. It comes with code, a clear formal style, a number of concisely stated facts and results." (Emmanuel Trucco, IEE Proceedings Vision, Image and Signal Processing, September, 2003)"This book presents an introduction to statistical signal processing. It mainly deals with the modelling and spectral estimation of wide sense stationary processes, and their filtering. ... This book is intended for graduate students, especially for students both in telecommunications and applied statistics. It can also serve as an excellent reference book for engineers, researchers and professors interested in statistical signal processing. I have found that the book is very helpful." (Yuehua Wu, Zentralblatt MATH, Vol. 1003 (3), 2003)
EAN: 9781852333850
ISBN: 1852333855
Untertitel: Modelling and Estimation. Softcover reprint of the original 1st ed. 2002. Book w. online files/update. Sprache: Englisch.
Verlag: Springer
Erscheinungsdatum: März 2002
Seitenanzahl: 352 Seiten
Übersetzer/Sprecher: Übersetzt von J. Ormrod
Format: kartoniert
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