|
|
|
|
| LEADER |
02575nam a22003137a 4500 |
| 001 |
95082 |
| 008 |
950427t19961996xxe ||| |||| 00| 0 eng d |
| 009 |
PPN023688327 |
| 020 |
|
|
|a 0133979857 (br.)
|
| 020 |
|
|
|a 013322760X
|
| 024 |
|
|
|a 9780133979855
|
| 041 |
0 |
|
|a eng
|
| 080 |
|
|
|a 621.391
|
| 082 |
|
|
|a 621.3815/324
|
| 100 |
1 |
|
|a Haykin, Simon,
|d 1931-
|
| 245 |
1 |
0 |
|a Adaptive filter theory
|c Simon Haykin,...
|
| 250 |
|
|
|a 3rd edition.
|
| 260 |
|
|
|a Upper Saddle River (N.J.) :
|b Prentice Hall.
|
| 260 |
|
|
|c C1996.
|
| 300 |
|
|
|a 1 vol. (xvii-989 p.) :
|b ill. ;
|c 24 cm.
|
| 490 |
1 |
|
|a Prentice Hall information and system sciences series
|
| 504 |
|
|
|a Bibliogr. p.941-977. Index. Glossaire
|
| 505 |
0 |
|
|a Introduction -- Part 1. Background materials -- Chapter 1. Discrete-time signal processing -- Chapter 2. Stationary processes and models -- Chapter 3. Spectrum analysis -- Chapter 4. Eigenanalysis -- Part 3. Linear optimum filtering -- Chapter 5. Wiener filters -- Chapter 6. Linear prediction -- Chapter 7. Kalman filters -- Part 3. Linear adaptative filtering -- Chapter 8. Method of steepest descent -- Chapter 9. Least-Mean-Square algorithm -- Chapter 10. Frequency-domain adaptative filters -- Chapter 11. Method of least squares -- Chapter 12. Rotation and reflections -- Chapter 13. Recursive least-squares algorithm -- Chapter 14. Square-root adaptative filters -- Chapter 15. Order recursive adaptative filters -- Chapter 16. Tracking of time-varying systems -- Chapter 17. Finite-precision effects -- Part 4. Nonlinear adaptative filtering -- Chapter 18. Blind deconvolution -- Chapter 19. Back-propagation learning -- Chapter 20. Radial basis function networks -- Appendix A : Complex variables -- Appendix B : Differentiation with respect to a vector -- Appendix C : Method of Lagrange multipliers -- Appendix D : Estimation theory -- Appendix E : Maximum entropy method -- Appendix F : Minimum-variance distortionless response spectrum -- Appendix G : Gradient adaptative Lattice algorithm -- Appendix H : Solution of the difference equation (9.75) -- Appendix I : Steady-state analysis of the LMS algorithm without invoking the independence assuption -- Appendix J : The complex wishart distribution
|
| 650 |
|
|
|a Théories non linéaires
|
| 650 |
|
|
|a Optimisation mathématique
|
| 650 |
|
|
|a Filtres (mathématiques)
|
| 650 |
|
|
|a Réseaux neuronaux (informatique)
|
| 650 |
|
|
|a Filtres adaptatifs
|
| 997 |
|
|
|0 95082
|1 Livre papier
|a Ressource papier
|c 0/Orléans/
|c 1/Orléans/BU Sciences, Technologies, STAPS/
|z Orléans, BU Sciences, Technologies, STAPS, F9108
|
