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Advances in Neural Networks: Computational and Theoretical Issues

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Advances in Neural Networks: Computational and Theoretical Issues/ edited by Simone Bassis, Anna Esposito, Francesco Carlo Morabito.
other author:	Bassis, Simone.
Description:	X, 402 p. 148 illus., 59 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-319-18164-6
ISBN:	9783319181646

Advances in Neural Networks: Computational and Theoretical Issues
Advances in Neural Networks: Computational and Theoretical Issues[electronic resource] /edited by Simone Bassis, Anna Esposito, Francesco Carlo Morabito. - 1st ed. 2015. - X, 402 p. 148 illus., 59 illus. in color.online resource. - Smart Innovation, Systems and Technologies,372190-3018 ;. - Smart Innovation, Systems and Technologies,37.

This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive, and context-aware Information Communication Technologies.

ISBN: 9783319181646

Standard No.: 10.1007/978-3-319-18164-6doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Advances in Neural Networks: Computational and Theoretical Issues
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