Complex Chebyshev-polynomial-based unified model (CCPBUM) neural networks

Jin-Tsong Jeng; Tsu-Tian Lee

doi:10.1117/12.304844

25 March 1998 Complex Chebyshev-polynomial-based unified model (CCPBUM) neural networks

Jin-Tsong Jeng, Tsu-Tian Lee

Proceedings Volume 3390, Applications and Science of Computational Intelligence; (1998) https://doi.org/10.1117/12.304844
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

In this paper, we propose complex Chebyshev Polynomial Based unified model neural network for the approximation of complex- valued function. Based on this approximate transformable technique, we have derived the relationship between the single-layered neural network and multi-layered perceptron neural network. It is shown that the complex Chebyshev Polynomial Based unified model neural network can be represented as a functional link network that are based on Chebyshev polynomial. We also derived a new learning algorithm for the proposed network. It turns out that the complex Chebyshev Polynomial Based unified model neural network not only has the same capability of universal approximator, but also has faster learning speed than conventional complex feedforward/recurrent neural network.

Citation Download Citation

Jin-Tsong Jeng and Tsu-Tian Lee "Complex Chebyshev-polynomial-based unified model (CCPBUM) neural networks", Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); https://doi.org/10.1117/12.304844

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