| Titre : | Statistical and Adaptive Signal Processing : spectral estimation, signal modeling, adaptive filtering and array processing | | Type de document : | texte imprimé | | Auteurs : | Dimitris G. Manolakis, Auteur ; Vinay K. Ingle, Auteur ; Stephen M. Kogon, Auteur | | Editeur : | Boston, London : Artech House | | Année de publication : | 2005 | | Collection : | Signal Processing | | Importance : | 796 | | Présentation : | couv. ill. en coul., ill. | | Format : | 28,8 cm. | | ISBN/ISSN/EAN : | 978-1-580-53610-3 | | Langues : | Anglais (eng) | | Catégories : | AUTOMATISME
| | Index. décimale : | 25-05 Application du traitement numérique du signal | | Résumé : | This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike.; From the fundamentals of discrete-time signal processing and linear signal models, to optimum linear filters and least-squares filtering and prediction, you get in-depth information on a broad range of critical topics from leading experts in industry and academia. This invaluable reference provides clear examples, problem sets, and computer experiments that help you master the material and learn how to implement various methods presented in the book. You also find a set of MATLAB functions that illustrate the use of various techniques and can be used to solve real-world problems in the field | | Note de contenu : | Contents
Preface.
1 Introduction.
2 Fundamentals of Discrete-Time Signal Processing.
3 Random Variables, Vectors, and Sequences.
4 Linear Signal Models.
5 Nonparametric Power Spectrum Estimation.
6 Optimum Linear Filters.
7 Algorithms and Structures for Optimum Linear Filters.
8 Least-Squares Filtering and Prediction.
9 Signal Modeling and Parametric Spectral Estimation.
10 Adaptive Filters.
11 Array Processing.
12 Further Topics.
Appendix A: Matrix Inversion Lemma.
Appendix B: Gradients and Optimization in Complex Space.
Appendix C: Matlab Functions.
Appendix D: Useful Results from Matrix Algebra.
Appendix E: Minimum Phase Test for Polynomials.
Bibliography.
Index. |
Statistical and Adaptive Signal Processing : spectral estimation, signal modeling, adaptive filtering and array processing [texte imprimé] / Dimitris G. Manolakis, Auteur ; Vinay K. Ingle, Auteur ; Stephen M. Kogon, Auteur . - Boston, London : Artech House, 2005 . - 796 : couv. ill. en coul., ill. ; 28,8 cm.. - ( Signal Processing) . ISBN : 978-1-580-53610-3 Langues : Anglais ( eng) | Catégories : | AUTOMATISME
| | Index. décimale : | 25-05 Application du traitement numérique du signal | | Résumé : | This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike.; From the fundamentals of discrete-time signal processing and linear signal models, to optimum linear filters and least-squares filtering and prediction, you get in-depth information on a broad range of critical topics from leading experts in industry and academia. This invaluable reference provides clear examples, problem sets, and computer experiments that help you master the material and learn how to implement various methods presented in the book. You also find a set of MATLAB functions that illustrate the use of various techniques and can be used to solve real-world problems in the field | | Note de contenu : | Contents
Preface.
1 Introduction.
2 Fundamentals of Discrete-Time Signal Processing.
3 Random Variables, Vectors, and Sequences.
4 Linear Signal Models.
5 Nonparametric Power Spectrum Estimation.
6 Optimum Linear Filters.
7 Algorithms and Structures for Optimum Linear Filters.
8 Least-Squares Filtering and Prediction.
9 Signal Modeling and Parametric Spectral Estimation.
10 Adaptive Filters.
11 Array Processing.
12 Further Topics.
Appendix A: Matrix Inversion Lemma.
Appendix B: Gradients and Optimization in Complex Space.
Appendix C: Matlab Functions.
Appendix D: Useful Results from Matrix Algebra.
Appendix E: Minimum Phase Test for Polynomials.
Bibliography.
Index. |
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