| Description |
1 online resource (xiii, 284 pages) : illustrations |
| Series |
Adaptive and learning systems for signal processing, communications, and control |
|
Adaptive and learning systems for signal processing, communications, and control.
|
| Contents |
Kalman filters / Simon Haykin -- Parameter-based Kalman filter training : theory and implementation / Gintaras V. Puskorius and Lee A. Feldkamp -- Learning shape and motion from image sequences / Gaurav S. Patel, Sue Becker, and Ron Racine -- Chaotic Dynamics / Gaurav S. Patel and Simon Haykin -- Dual extended Kalman filter methods / Eric A. Wan and Alex T. Nelson -- Learning nonlinear dynamical systems using the expectation-maximization algorithm / Sam Roweis and Zoubin Ghahramani -- The unscented Kalman filter / Eric A. Wan and Rudolph van der Merwe |
| Summary |
This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear |
| Notes |
"A Wiley Interscience publication." |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Kalman filtering.
|
|
Neural networks (Computer science)
|
| Form |
Electronic book
|
| Author |
Haykin, Simon S., 1931-
|
| ISBN |
0471221546 |
|
0471369985 (alk. paper) |
|
047146421X (electronic bk.) |
|
9780471221548 |
|
9780471369981 |
|
9780471464211 (electronic bk.) |
|
