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Recurrent Neural
Networks
Xiaolin Hu and P.
Balasubramaniam
Recurrent Neural Networks
Edited by Xiaolin Hu and P. Balasubramaniam
ISBN 978-953-7619-08-4, 400 pages,  Publishing date: September 2008
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The concept of neural network originated from neuroscience, and one of its primitive aims is to help us understand the principle of the central nerve system and related behaviors through mathematical modeling. The first part of the book is a collection of three contributions dedicated to this aim. The second part of the book consists of seven chapters, all of which are about system identification and control. The third part of the book is composed of Chapter 11 and Chapter 12, where two interesting RNNs are discussed, respectively.The fourth part of the book comprises four chapters focusing on optimization problems. Doing optimization in a way like the central nerve systems of advanced animals including humans is promising from some viewpoints.

Table of Contents

01 Aperiodic (Chaotic) Behavior in RNN with Homeostasis as a Source of Behavior Novelty: Theory and Applications
Jorge Simão
Downloads 281
02 Biological Signals Identification by a Dynamic Recurrent Neural Network: from Oculomotor Neural Integrator to Complex Human Movements and Locomotion
Guy Cheron, Françoise Leurs, Ana Bengoetxea, Ana Maria Cebolla, Jean-Philippe Draye, Pablo D’alcantara and Bernard Dan
Downloads 247
03 Linguistic Productivity and Recurrent Neural Networks
Akito Sakurai and Yoshihisa Shinozawa
Downloads 244
04 Recurrent Neural Network Identification and Adaptive Neural Control of Hydrocarbon Biodegradation Processes
Ieroham Baruch, Carlos Mariaca-Gaspar and Josefina Barrera-Cortes
Downloads 321
06 Recurrent Fuzzy Neural Networks and Their Performance Analysis
R.A. Aliev, B. Fazlollahi, B.G. Guirimov and R.R. Aliev
Downloads 311
07 Recurrent Interval Type-2 Fuzzy Neural Network Using Asymmetric Membership Functions
Ching-Hung Lee and Tzu-Wei Hu
Downloads 326
08 Rollover Control in Heavy Vehicles via Recurrent High Order Neural Networks
Luis J. Ricalde, Edgar N. Sanchez, Reza Langari and Danial Shahmirzadi
Downloads 247
10 Application of Recurrent Neural Networks to Rainfall-runoff Processes
Tsung-yi Pan, Ru-yih Wang, Jihn-sung Lai and Hwa-lung Yu
Downloads 324
11 Recurrent Neural Approach for Solving Several Types of Optimization Problems
Ivan N. da Silva, Wagner C. Amaral, Lucia V. Arruda and Rogerio A. Flauzino
Downloads 235
12 Applications of Recurrent Neural Networks to Optimization Problems
Alaeddin Malek
Downloads 445
13 Neurodynamic Optimization: Towards Nonconvexity
Xiaolin Hu
Downloads 206
14 An Improved Extremum Seeking Algorithm Based on the Chaotic Annealing Recurrent Neural Network and Its Application
Yun-an Hu, Bin Zuo and Jing Li
Downloads 225
16 Dynamics of Two-Dimensional Discrete-Time Delayed Hopfield Neural Networks
Eva Kaslik and Ştefan Balint
Downloads 225
17 Case Studies for Applications of Elman Recurrent Neural Networks
Elif Derya Übeyli and Mustafa Übeyli
Downloads 435
18 Partially Connected Locally Recurrent Probabilistic Neural Networks
Todor D. Ganchev, Konstantinos E. Parsopoulos, Michael N. Vrahatis and Nikos D. Fakotakis
Downloads 355