Models of Neural Networks III by Eytan Domany
One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, Global Analysis of Recurrent Neural Net- works, by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and- fire neurons with local interactions. The chapter, Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu- ment since has been shown to be rather susceptible to generalization.| SKU | Unavailable |
| ISBN 13 | 9780387943688 |
| ISBN 10 | 0387943684 |
| Title | Models of Neural Networks III |
| Author | Eytan Domany |
| Series | Physics Of Neural Networks |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer-Verlag New York Inc. |
| Year published | 1995-12-01 |
| Number of pages | 311 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |