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Normalized exponential neural networks

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Abstract

In this paper, the normalized exponential neural network (ENN) is studied. It is proved that ENN is a universal approximator. The stability relation between systems and neural networks working as controllers is investigated. The results show that when designing a system, one should firstly consider system stability rather than controller stability. Accordingly, a new hybrid learning algorithm is presented, and it is proved that this algorithm eventually converge to equilibria.

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Authors and Affiliations

  1. Department of Computer, Royal Holloway College, University of London, London, UK

    Wang Shitong

  2. Department Computer, East China Shipbuilding Institute, 212003, Zhengjiang, P.R. China

    Wang Shitong

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  1. Wang Shitong
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Wang Shitong is a Professor and the head of the Department of Computer at East China Shipbuilding Institute. Up to now, he has published 5 books and 92 papers in international/national journals or in international conferences. His research interests include artificial intelligence, neural networks, fuzzy system and rough set theory.

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Wang, S. Normalized exponential neural networks. J. of Comput. Sci. & Technol. 13, 375–383 (1998). https://doi.org/10.1007/BF02946626

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  • DOI: https://doi.org/10.1007/BF02946626

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