This book is a comprehensive introduction to the neural network models currently under intensive study for computational applications. It is a detailed, logically-developed treatment that covers the theory and uses of collective computational networks, including associative memory, feed forward networks, and unsupervised learning. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.
This book is a comprehensive introduction to the neural network models currently under intensive study for computational applications. It is a detailed, logically-developed treatment that covers the theory and uses of collective computational networks, including associative memory, feed forward networks, and unsupervised learning. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.
About the Santa Fe Institute Santa Fe Institute Editorial Board September 1990 Santa Fe Institute Studies in the Sciences of Complexity Series Foreword Foreword Foreword Preface Introduction The Hopfield Model Extensions of the Hopfield Model Optimization Problems Simple Perceptrons Multi-Layer Networks Recurrent Networks Unsupervised Hebbian Learning Unsupervised Competitive Learning Formal Statistical Mechanics of Neural Networks Statistical Mechanics
About the Santa Fe Institute Santa Fe Institute Editorial Board September 1990 Santa Fe Institute Studies in the Sciences of Complexity Series Foreword Foreword Foreword Preface Introduction The Hopfield Model Extensions of the Hopfield Model Optimization Problems Simple Perceptrons Multi-Layer Networks Recurrent Networks Unsupervised Hebbian Learning Unsupervised Competitive Learning Formal Statistical Mechanics of Neural Networks Statistical Mechanics
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Shop der buecher.de GmbH & Co. KG Bürgermeister-Wegele-Str. 12, 86167 Augsburg Amtsgericht Augsburg HRA 13309