© 2004

Convergence Analysis of Recurrent Neural Networks


Part of the Network Theory and Applications book series (NETA, volume 13)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Zhang Yi, K. K. Tan
    Pages 1-14
  3. Zhang Yi, K. K. Tan
    Pages 15-32
  4. Zhang Yi, K. K. Tan
    Pages 33-67
  5. Zhang Yi, K. K. Tan
    Pages 91-117
  6. Zhang Yi, K. K. Tan
    Pages 195-217
  7. Back Matter
    Pages 219-233

About this book


Since the outstanding and pioneering research work of Hopfield on recurrent neural networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong interests in scientists and researchers. Recent years have recorded a remarkable advance in research and development work on RNNs, both in theoretical research as weIl as actual applications. The field of RNNs is now transforming into a complete and independent subject. From theory to application, from software to hardware, new and exciting results are emerging day after day, reflecting the keen interest RNNs have instilled in everyone, from researchers to practitioners. RNNs contain feedback connections among the neurons, a phenomenon which has led rather naturally to RNNs being regarded as dynamical systems. RNNs can be described by continuous time differential systems, discrete time systems, or functional differential systems, and more generally, in terms of non­ linear systems. Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs.


calculus cognition image processing linear optimization network networks neural networks pattern recognition

Authors and affiliations

  1. 1.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduPeople’s Republic of China
  2. 2.Department of Electrical and Computer EngineeringThe National University of SingaporeSingapore

Bibliographic information

  • Book Title Convergence Analysis of Recurrent Neural Networks
  • Authors Zhang Yi
  • Series Title Network Theory and Applications
  • DOI
  • Copyright Information Springer-Verlag US 2004
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Hardcover ISBN 978-1-4020-7694-7
  • Softcover ISBN 978-1-4757-3821-6
  • eBook ISBN 978-1-4757-3819-3
  • Series ISSN 1568-1696
  • Edition Number 1
  • Number of Pages XVII, 233
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Mathematics of Computing
    Systems Theory, Control
    Electrical Engineering
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