Artificial Adaptive Systems Using Auto Contractive Maps: Theory, Applications and Extensions

by Paolo Massimo Buscema, Giulia Massini, Marco Breda, Weldon A. Lodwick, Francis Newman

Overview

This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks.

The book’s primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the “spin-net,” as a dynamic form of auto-associative memory.

Product Details

ISBN-13:	9783030091354
Publisher:	Springer International Publishing
Publication date:	12/25/2018
Series:	Studies in Systems, Decision and Control , #131
Edition description:	Softcover reprint of the original 1st ed. 2018
Pages:	179
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

An Introduction.- Artificial Neural Networks.- Auto-Contractive Maps.- Visualization of Auto-CM Output.- Dataset Transformations and Auto-CM.- Comparison of Auto-CM to Various Other Data Understanding Approaches.