Overview
- Highlights the ability of Neural Networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR)
- Defines a new neural-network-based method for learning image similarity and explains how to use fuzzy Gaussian neural networks to predict personality
- Describes the design of a new model of fuzzy nonlinear perceptron based on alpha level sets
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 661)
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Table of contents (8 chapters)
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Front Matter
Keywords
About this book
It introduces the fuzzy Clifford Gaussian network, and two concurrent neural models: (1) concurrent fuzzy nonlinear perceptron modules, and (2) concurrent fuzzy Gaussian neural network modules.
Furthermore, it explains the design of a new model of fuzzy nonlinear perceptron based on alpha level sets and describes a recurrent fuzzy neural network model with a learning algorithm based on the improved particle swarm optimization method.
Authors and Affiliations
Bibliographic Information
Book Title: Issues in the Use of Neural Networks in Information Retrieval
Authors: Iuliana F. Iatan
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-43871-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-43870-2Published: 07 October 2016
Softcover ISBN: 978-3-319-82930-2Published: 15 June 2018
eBook ISBN: 978-3-319-43871-9Published: 28 September 2016
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIX, 199
Number of Illustrations: 44 b/w illustrations, 44 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Mathematical Models of Cognitive Processes and Neural Networks, Pattern Recognition