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A neural network model of a communication network with information servers

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Abstract

This paper models information flow in a communication network. The network consists of nodes that communicate with each other, and information servers that have a predominantly one-way communication to their customers. A neural network is used as a model for the communication network. The existence of multiple equilibria in the communication network is established. The network operator observes only one equilibrium, but if he knows the other equilibria, he can influence the free parameters, for example by providing extra bandwidth, so that the network settles in another equilibrium that is more profitable for the operator. The influence of several network parameters on the dynamics is studied both by simulation and by theoretical methods.

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References

  1. De Wilde P. Non-linear dynamics of two types of networks with intelligent nodes. BT Technology J 1996; 14(4): 98–104.

    Google Scholar 

  2. De Wilde P. Neural Network Models (second expanded edition). Springer-Verlag, 1997.

  3. Amit DJ. Modeling Brain Function, The World of Attractor Neural Networks. Cambridge University Press, 1989.

  4. Vilela Mendes R, Taborda Duarte J. Vector fields and neural networks. Complex Systems 1992; 6: 21–30.

    Google Scholar 

  5. Cohen MA, Grossberg S. Absolute stability of global pattern-formation and parallel memory storage by competitive neural networks. IEEE Trans Systems, Man and Cybernetics 1983; 13(5): 815–826.

    Google Scholar 

  6. van Hemmen JL, Grensing D, Huber A, Kühn R. Nonlinear neural networks. I. General theory. J Statistical Physics 1988; 50(1/2): 231–257.

    Google Scholar 

  7. De Wilde P. The size of the diagonal elements in neural networks. Neural Networks 1997; 10(3): 499–504.

    Google Scholar 

  8. Bruce AD, Gardner EJ, Wallace DJ. Dynamics and statistical mechanics of the Hopfield model. J Physics A: Mathematical and General 1987; 20: 2909–2934.

    Google Scholar 

  9. Papoulis A. Probability, Random Variables, and Stochastic Processes. McGraw-Hill, 1981.

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Imperial College of Science, Technology and Medicine, SW7 2BT, London, UK

    P. De Wilde

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  1. P. De Wilde
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Additional information

The author was with the Intelligent Systems Unit, BT Laboratories, Martlesham Heath, Ipswich IP5 7RE, UK.

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De Wilde, P. A neural network model of a communication network with information servers. Neural Comput & Applic 7, 26–36 (1998). https://doi.org/10.1007/BF01413707

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  • DOI: https://doi.org/10.1007/BF01413707

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