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.
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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.
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Taschenbuch. Zustand: Neu. Blind Equalizers By Techniques Of Optimal Non-Linear Filtering Theory | Analysis and Derivation | Monika Pinchas | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639155303 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Artikel-Nr. 101563378
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