Open access peer-reviewed Edited Volume

Recurrent Neural Networks

Edited by Xiaolin Hu

Tsinghua University, China


P. Balasubramaniam

Gandhigram Rural Institute, India

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.

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Recurrent Neural NetworksEdited by Xiaolin Hu

Published: September 1st 2008

DOI: 10.5772/68

ISBN: 978-953-7619-08-4

eBook (PDF) ISBN: 978-953-51-5795-3

Copyright year: 2008

Books open for chapter submissions

46306 Total Chapter Downloads

18 Crossref Citations

21 Web of Science Citations

28 Dimensions Citations


Open access peer-reviewed

1. Aperiodic (Chaotic) Behavior in RNN with Homeostasis as a Source of Behavior Novelty: Theory and Applications

By Jorge Simão


Open access peer-reviewed

2. Biological Signals Identification by a Dynamic Recurrent Neural Network: from Oculomotor Neural Integrator to Complex Human Movements and Locomotion

By Guy Cheron, Françoise Leurs, Ana Bengoetxea, Ana Maria Cebolla, Jean-Philippe Draye, Pablo D’alcantara and Bernard Dan


Open access peer-reviewed

3. Linguistic Productivity and Recurrent Neural Networks

By Akito Sakurai and Yoshihisa Shinozawa


Open access peer-reviewed

4. Recurrent Neural Network Identification and Adaptive Neural Control of Hydrocarbon Biodegradation Processes

By Ieroham Baruch, Carlos Mariaca-Gaspar and Josefina Barrera-Cortes


Open access peer-reviewed

5. Design of Self-Constructing Recurrent-Neural-Network-Based Adaptive Control

By Chun-Fei Hsu and Chih-Min Lin


Open access peer-reviewed

6. Recurrent Fuzzy Neural Networks and Their Performance Analysis

By R.A. Aliev, B. Fazlollahi, B.G. Guirimov and R.R. Aliev


Open access peer-reviewed

7. Recurrent Interval Type-2 Fuzzy Neural Network Using Asymmetric Membership Functions

By Ching-Hung Lee and Tzu-Wei Hu


Open access peer-reviewed

8. Rollover Control in Heavy Vehicles via Recurrent High Order Neural Networks

By Luis J. Ricalde, Edgar N. Sanchez, Reza Langari and Danial Shahmirzadi


Open access peer-reviewed

9. A New Supervised Learning Algorithm of Recurrent Neural Networks and L2 Stability Analysis in Discrete-Time Domain

By Wu Yilei, Yang Xulei and Song Qing


Open access peer-reviewed

10. Application of Recurrent Neural Networks to Rainfall-runoff Processes

By Tsung-yi Pan, Ru-yih Wang, Jihn-sung Lai and Hwa-lung Yu


Open access peer-reviewed

11. Recurrent Neural Approach for Solving Several Types of Optimization Problems

By Ivan N. da Silva, Wagner C. Amaral, Lucia V. Arruda and Rogerio A. Flauzino


Open access peer-reviewed

12. Applications of Recurrent Neural Networks to Optimization Problems

By Alaeddin Malek


Open access peer-reviewed

13. Neurodynamic Optimization: towards Nonconvexity

By Xiaolin Hu


Open access peer-reviewed

14. An Improved Extremum Seeking Algorithm Based on the Chaotic Annealing Recurrent Neural Network and Its Application

By Yun-an Hu, Bin Zuo and Jing Li


Open access peer-reviewed

15. Stability Results for Uncertain Stochastic High-Order Hopfield Neural Networks with Time Varying Delays

By P. Balasubramaniam and R. Rakkiyappan


Open access peer-reviewed

16. Dynamics of Two-Dimensional Discrete-Time Delayed Hopfield Neural Networks

By Eva Kaslik and Ştefan Balint


Open access peer-reviewed

17. Case Studies for Applications of Elman Recurrent Neural Networks

By Elif Derya Übeyli and Mustafa Übeyli


Open access peer-reviewed

18. Partially Connected Locally Recurrent Probabilistic Neural Networks

By Todor D. Ganchev, Konstantinos E. Parsopoulos, Michael N. Vrahatis and Nikos D. Fakotakis


Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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