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Blind Equalizers By Techniques Of Optimal Non-Linear Filtering Theory: Analysis and Derivation - Softcover
Synopsis
Blind deconvolution, fundamental in signal processing applications, is a challenging problem. Although blind equalization is essentially a nonlinear filtering problem, it has not yet been treated by all the well known advanced techniques of optimal non-linear filtering theory. In this book we use the Edgeworth expansion, maximum entropy argumentations and the Laplace integral method in order to obtain two new groups of blind deconvolution methods which outperform the old and new algorithms. The proposed methods are based on new, closed formed approximated expressions for the conditional expectation suitable for the blind deconvolution problem. Since these expressions do not impose any restrictions (except that of even symmetric) on the probability distribution of the (unobserved) input sequence, they are suitable for a wider range of source pdf compared to Bellini's, Fiori's or Haykin's expression. The derivation of the above mentioned equalizers are accompanied by theoretical analysis of the performance in the mean square error (MSE) sense and are justified via simulation. These new methods are useful to professionals in Communications who seek for improved equalization methods.
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About the Author
Monika Pinchas, PhD: Studied Electrical Engineering at Tel-Aviv University. Lecturer at Ariel University Center of Samaria Israel. Research interests: Blind deconvolution/equalization and synchronization. In the past served as the CTO at Resolute Networks. Included in the 10th Anniversary Edition of "Marquis Who's Who in Science and Engineering.
"About this title" may belong to another edition of this title.
- PublisherVDM Verlag
- Publication date2009
- ISBN 10 3639155300
- ISBN 13 9783639155303
- BindingPaperback
- LanguageEnglish
- Number of pages96
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Blind deconvolution, fundamental in signal processingapplications, is a challenging problem. Althoughblind equalization is essentially a nonlinearfiltering problem, it has not yet been treated by allthe well known advanced techniques of optimalnon-linear filtering theory. In this book we use theEdgeworth expansion, maximum entropy argumentationsand the Laplace integral method in order to obtaintwo new groups of blind deconvolution methods whichoutperform the old and new algorithms. The proposedmethods are based on new, closed formed approximatedexpressions for the conditional expectation suitablefor the blind deconvolution problem. Since theseexpressions do not impose any restrictions (exceptthat of even symmetric) on the probabilitydistribution of the (unobserved) input sequence, theyare suitable for a wider range of source pdf comparedto Bellini's, Fiori's or Haykin's expression. Thederivation of the above mentioned equalizers areaccompanied by theoretical analysis of theperformance in the mean square error (MSE) sense andare justified via simulation. These new methods areuseful to professionals in Communications who seekfor improved equalization methods. Seller Inventory # 9783639155303
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