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Recursive neural networks for signal processing and control

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/20419

Recursive neural networks for signal processing and control

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Title: Recursive neural networks for signal processing and control
Author: Abdallah, Chaouki T.; Hush, Don; Horne, B.
Subject(s): Multilayer perceptrons
Neural networks
Nonlinear control systems
Abstract: The authors describe a special type of dynamic neural network called the recursive neural network (RNN). The RNN is a single-input single-output nonlinear dynamical system with a nonrecursive subnet and two recursive subnets arranged in the configuration shown. The authors describe the architecture of the RNN, present a learning algorithm for the network, and provide some examples of its use.
Date: 1991
Publisher: IEEE
Citation: Proceedings of the 1991 IEEE Workshop Neural Networks for Signal Processing [1991]: 523-532
Description: Digital Object Identifier : 10.1109/NNSP.1991.239489
URI: http://hdl.handle.net/1928/20419
ISBN: 0-7803-0118-8

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