Reviews for Hebbian Learning and Negative Feedback Networks

The average rating for Hebbian Learning and Negative Feedback Networks based on 2 reviews is 3.5 stars.

Review # 1 was written on 2018-03-29 00:00:00 R. Priest Published by John Wiley & Son, 2007 The author of this book Robert A. Dunne, PhD, is Research Scientist in the Mathematical and Information Sciences Division of the Commonwealth Scientific and Industrial Research Organization (CSIRO) in North Ryde, Australia. Dr. Dunne received his PhD from Murdoch University, and his research interests include remote sensing and bioinformatics This book provides an excellent introduction to neutral networks from a statistical perspective. Even tough statistic is not easy to understand easily, this book successful connects logistic regression and linear discriminant analysis, thus making it critical reference and self-study guide for students and professionals alike in the fields of mathematics, statistics, computer science, and electrical engineering. This book organized into 13 chapters : 1 Introduction 2 The Multi-Layer Perceptron Model 3 Linear Discriminant Analysis 4 Activation and Penalty Functions 5 Model Fitting and Evaluation 6 The Task-based MLP 7 Incorporating Spatial Information into an MLP Classifier 8 Influence Curves for the Multi-layer Perceptron Classifier 9 The Sensitivity Curves of the MLP Classifier 10 A Robust Fitting Procedure for MLP Models 11 Smoothed Weights 12 Translation Invariance 13 Fixed-slope Training As statistic and neural network book, this book is easy enogh to understand.

Review # 2 was written on 2009-04-22 00:00:00 Stefanos Skourvoulianakis Fascinating read but quite outdated