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OverviewThis 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. Full Product DetailsAuthor: Paolo Massimo Buscema , Giulia Massini , Marco Breda , Weldon A. LodwickPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 1st ed. 2018 Volume: 131 Weight: 0.454kg ISBN: 9783319750484ISBN 10: 3319750488 Pages: 179 Publication Date: 06 March 2018 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsAn 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.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |