Artificial Intelligence Systems Based on Hybrid Neural Networks - Theory and Applications (Paperback, 1st ed. 2021)

This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 904
Release date:	September 2021
First published:	2021
Authors:	Michael Zgurovsky • Victor Sineglazov • Elena Chumachenko
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	512
Edition:	1st ed. 2021
ISBN-13:	978-3-03-048455-2
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-03-048455-6
Barcode:	9783030484552

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