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Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applicationsby Ming Zhang
Synopses & Reviews
Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks. Since HONNs are open box models, they can be easily used in information science, information technology, management, economics, and business. This book details the techniques, theory and applications essential to engaging and capitalizing on this developing technology.
Book News Annotation:
This collection introduces higher order neural network (HONN) group models and adaptive HONNs for simulating nonlinear data. The computer science chapters describe adaptive tolerance trees for translation-invariant face recognition, symbolic computations, evolutionary algorithms, a neural controller for nonlinear systems, and data mining applications. The computer engineering chapters review 50 years of electronic hardware implementations and investigate the training of networks using back propagation and Levenberg-Marquardt algorithms, neural observers for anaerobic processes, and electrical machine excitation control. Zhang is a computer science professor at Christopher Newport University in Virginia. Annotation ©2010 Book News, Inc., Portland, OR (booknews.com)
"This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.
Table of Contents
18. Identification of nonlinear systems using a new neuro-fuzzy dynamical system definition based on high order neural network function approximators — 19. Neuro - fuzzy control schemes based on high order neural network function approximators — 20. Back-stepping control of quadrotor — 21. Artificial tactile sensing and robotic surgery using higher order neural networks — 22. A theoretical and empirical study of functional link neural networks (FLANNs) for classification.
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