A Neural Network with Evolutionary Neurons

Authors:
Alberto Alvarez
Affiliations:
North Atlantic Treaty Organization, SACLANT Undersea Research Centre, Viale San Bartolomeo 400, 19138 La Spezia, Italy. E-mail: alvarez@saclantc.nato.int
Venue:
Neural Processing Letters
Year:
2002

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Abstract

A neural network, combining evolution and learning is introduced. The novel feature of the proposed network is the evolutionary character of its neurons. The argument of the transfer function performed by the neurons in the network is neither a linear nor polynomial function of the inputs to the neuron, but an unknown general function P(·). The adequate functional form P(·) for each neuron, is achieved during the learning period by means of genetic programming. The proposed neural network is applied to the problem domain of time series prediction of the Mackey-Glass delay differential equation. Simulation results indicate that the new neural network is effective.