carnevalemanfredonia.it
» » Discrete Stochastic Processes and Optimal Filtering (Digital Signal and Image Processing)

eBook Discrete Stochastic Processes and Optimal Filtering (Digital Signal and Image Processing) download

by Jean-Claude Bertein,Roger Ceschi

eBook Discrete Stochastic Processes and Optimal Filtering (Digital Signal and Image Processing) download ISBN: 1848211813
Author: Jean-Claude Bertein,Roger Ceschi
Publisher: Wiley-ISTE; 2 edition (January 26, 2010)
Language: English
Pages: 320
ePub: 1836 kb
Fb2: 1399 kb
Rating: 4.2
Other formats: lrf lit rtf mbr
Category: Engineering
Subcategory: Engineering

Roger Ceschi is an ENSEA engineer and holds a Master’s and PhD degree from the University of Paris XI. He was formerly Director of the ENSEA and today he is Director General of the ESIEE Amiens.

Jean-Claude Bertein, Roger Ceschi

Jean-Claude Bertein, Roger Ceschi. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using Matlab.

Jean-Claude Bertein has a Master's and PhD degree from the University of Paris VI.

by Jean-Claude Bertein (Author), Roger Ceschi (Author). Jean-Claude Bertein has a Master's and PhD degree from the University of Paris VI.

Exercises with solutions punctuate each chapter, and practical examples are given using Matlab software.

by Jean-Claude Bertein, Roger Ceschi.

Jean-Claude Bertein, Roger Ceschi. ISBN: 978-1-905-20974-3 May 2007 Wiley-ISTE 287 Pages.

Jean-Claude Bertein Roger Ceschi. Series: Digital Signal & Image Processing Series (ISTE-DSP). File: PDF, . 2 MB. Читать онлайн.

Home Jean-Claude Bertein Discrete Stochastic Processes and Optimal .

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using MATLAB.