Principles of adaptive filters and self-learning systems
Kalman and Wiener Filters, Neural Networks, Genetic Algorithms and Fuzzy Logic Systems Together in One Text Book How can a signal be processed for which there are few or no a priori data? Professor Zaknich provides an ideal textbook for one-semester introductory graduate or senior undergraduate cour...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
London :
Springer London
2005.
Cham : Springer Nature |
| Schriftenreihe: | Advanced Textbooks in Control and Signal Processing
|
| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Anmerkung: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Principles of Adaptive Filters and Self-learning Systems, Texte imprimé, 9781848008830 • Principles of Adaptive Filters and Self-learning Systems, Texte imprimé, 9781852339845 |
Inhaltsangabe:
- Adaptive Filtering
- Linear Systems and Stochastic Processes
- Modelling
- Optimisation and Least Squares Estimation
- Parametric Signal and System Modelling
- Classical Filters and Spectral Analysis
- Optimum Wiener Filter
- Optimum Kalman Filter
- Power Spectral Density Analysis
- Adaptive Filter Theory
- Adaptive Finite Impulse Response Filters
- Frequency Domain Adaptive Filters
- Adaptive Volterra Filters
- Adaptive Control Systems
- Nonclassical Adaptive Systems
- to Neural Networks
- to Fuzzy Logic Systems
- to Genetic Algorithms
- Adaptive Filter Application
- Applications of Adaptive Signal Processing
- Generic Adaptive Filter Structures.