Indholdsfortegnelse: Adaptive filter theory

Enregistré dans:

Bibliografiske detaljer
Hovedforfatter:	Haykin, Simon, 1931-
Format:	Livre papier
Sprog:	Anglais
Udgivet:	Upper Saddle River (N.J.) : Prentice Hall C1996.
Udgivelse:	3rd edition.
Serier:	Prentice Hall information and system sciences series
Fag:	Théories non linéaires Optimisation mathématique Filtres (mathématiques) Réseaux neuronaux (informatique) Filtres adaptatifs
Autres localisations:	Voir dans le Sudoc

Indholdsfortegnelse:

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