Mathematical methods and algorithms for signal processing / Todd K. Moon (N.J.)

Public ISBD Titre : Mathematical methods and algorithms for signal processing Type de document : texte imprime Auteurs : Todd K. Moon ; Stirling Wynn C Editeur : Upper Saddle River : Prentice Hall Année de publication : N.J. Importance : (XXXVI-937 p.) Présentation : ill. Format : 26 cm + CD ISBN/ISSN/EAN : 978-0-201-36186-5 Note générale : Bibliogr. p. [915]-928. Index Langues : Anglais Mots-clés : Traitement du signal  Algorithmes Résumé : Sommaire : I. Introduction and foundations II. Vector spaces and linear algebra 2. Signal spaces 3. Representation and approximation in vector spaces 4. Linear operators and matrix inverses 5. Some important matrix factorizations 6. Eigenvalues and Eigenvectors 7. The singular value decomposition [SVD] 8. Some special matrices and their applications 9. Kronecker products and the Vec operator III. Detection, estimation, and optimal filtering 10. Introduction to detection and estimation, and mathematical notation 11. Detection theory 12. Estimation theory 13. The Kalman filter IV. Iterative and recursive methods in signal processing 14. Basic concepts and methods of iterative algorithms 15. Iteration by composition of mappings 16. Other iterative algorithms 17. The EM algorithm in signal processing V. Methods of optimization 18. Theory of constrained optimization 19. Shortest-path algorithms and dynamic programming 20. Linear programming. Appendices : basic concepts and definitions ; completing the square ; basic matrix concepts ; random processes ; derivatives and gradients ; conditional expectations of multinomial and Poisson r.v.s. Permalink : ./index.php?lvl=notice_display&id=11610 Mathematical methods and algorithms for signal processing [texte imprime] / Todd K. Moon ; Stirling Wynn C . - Upper Saddle River : Prentice Hall, N.J. . - (XXXVI-937 p.) : ill. ; 26 cm + CD. ISBN : 978-0-201-36186-5 Bibliogr. p. [915]-928. Index Langues : Anglais Mots-clés : Traitement du signal  Algorithmes Résumé : Sommaire : I. Introduction and foundations II. Vector spaces and linear algebra 2. Signal spaces 3. Representation and approximation in vector spaces 4. Linear operators and matrix inverses 5. Some important matrix factorizations 6. Eigenvalues and Eigenvectors 7. The singular value decomposition [SVD] 8. Some special matrices and their applications 9. Kronecker products and the Vec operator III. Detection, estimation, and optimal filtering 10. Introduction to detection and estimation, and mathematical notation 11. Detection theory 12. Estimation theory 13. The Kalman filter IV. Iterative and recursive methods in signal processing 14. Basic concepts and methods of iterative algorithms 15. Iteration by composition of mappings 16. Other iterative algorithms 17. The EM algorithm in signal processing V. Methods of optimization 18. Theory of constrained optimization 19. Shortest-path algorithms and dynamic programming 20. Linear programming. Appendices : basic concepts and definitions ; completing the square ; basic matrix concepts ; random processes ; derivatives and gradients ; conditional expectations of multinomial and Poisson r.v.s. Permalink : ./index.php?lvl=notice_display&id=11610

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