Convergence Analysis of Recurrent Neural Networks

✍ Scribed by Zhang Yi, K. K. Tan (auth.)

Publisher: Springer US
Year: 2004
Tongue: English
Leaves: 244
Series: Network Theory and Applications 13
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xvii
Introduction....Pages 1-14
Hopfield Recurrent Neural Networks....Pages 15-32
Cellular Neural Networks....Pages 33-67
Recurrent Neural Networks with Unsaturating Piecewise Linear Activation Functions....Pages 69-89
Lotka-Volterra Recurrent Neural Networks with Delays....Pages 91-117
Delayed Recurrent Neural Networks with Global Lipschitz Activation Functions....Pages 119-170
Other Models of Continuous Time Recurrent Neural Networks....Pages 171-193
Discrete Recurrent Neural Networks....Pages 195-217
Back Matter....Pages 219-233

✦ Subjects

Mathematics of Computing; Systems Theory, Control; Electrical Engineering

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