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DEPRETTERE, SVD AND SIGNAL PROCESSING


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ISBN: Ostalo
Godina izdanja: 1988
Oblast: Elektrotehnika
Jezik: Engleski
Autor: Strani

Compiled in this book is a selection of articles written by internationally recognized experts in the fields of matrix computation and signal processing. In almost all digital signal processing (DSR) problems, the available data is corrupted by (measurement) noise or is incomplete. Classical techniques are unable to separate "signal" spaces and "noise" spaces. However, the information hidden in the data can be made explicit through singular value decomposition (SVD). SVD based signal processing is making headway and will become feasible soon, thanks to the progress in parallel computations and VLSI implementation. The book is divided into six parts. Part one is a tutorial, beginning with an introduction, including (VLSI) parallel algorithms and some intriguing problems. It describes several applications of SVD in system identification and signal detection. It also deals with the fundamental harmonic retrieval problem and principal component analysis. Part two discusses details of model reduction, system identification and detection of multiple sinusoids in white noise, while part three is devoted to the total-least-squares and generalized singular value decomposition problems

Predmete ne šaljem pouzećem, jedino nakon uplate. Knjige ne šaljem kao obična tiskovina, jedino kao preporučena tiskovina. Imam puno knjiga i ne mogu da garantujem da su sve na stanju, ponekad se zagube i u tom smislu bih vas zamolio za razumevanje, ako se to desi. U inostranstvo ne šaljem antikvarne knjige. Lično preuzimanje je na mojoj kućnoj adresi (nalazim se u širem centru, u blizini bivše Lutrije Vojvodine.

Predmet: 81960517
Compiled in this book is a selection of articles written by internationally recognized experts in the fields of matrix computation and signal processing. In almost all digital signal processing (DSR) problems, the available data is corrupted by (measurement) noise or is incomplete. Classical techniques are unable to separate "signal" spaces and "noise" spaces. However, the information hidden in the data can be made explicit through singular value decomposition (SVD). SVD based signal processing is making headway and will become feasible soon, thanks to the progress in parallel computations and VLSI implementation. The book is divided into six parts. Part one is a tutorial, beginning with an introduction, including (VLSI) parallel algorithms and some intriguing problems. It describes several applications of SVD in system identification and signal detection. It also deals with the fundamental harmonic retrieval problem and principal component analysis. Part two discusses details of model reduction, system identification and detection of multiple sinusoids in white noise, while part three is devoted to the total-least-squares and generalized singular value decomposition problems 81960517 DEPRETTERE, SVD AND SIGNAL PROCESSING

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