Download Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks PDF EPUB
Author: Russell Reed
Pages: 352
Size: 2.307,84 Kb
Publication Date: March 26,1999
Category: Neural Networks
Artificial neural networks are non-linear mapping systems whose structure is usually loosely predicated on principles seen in the anxious systems of human beings and animals. The essential idea is that substantial systems of simple devices linked together in suitable methods can generate many complicated and interesting behaviors. The reserve may be used as an instrument kit by readers thinking about applying networks to particular problems, yet in addition, it presents theory and references outlining the last a decade of MLP analysis.
This book presents a thorough and practical summary of almost every facet of MLP methodology, progressing from a short debate of what MLPs are and how they could be utilized to an in-depth study of technical elements affecting performance. They are the mostly trusted neural systems, with applications as varied as finance (forecasting), production (process control), and technology (speech and image reputation). This book targets the subset of feedforward artificial neural systems known as multilayer perceptrons (MLP).