A Neural Network that uses Evolutionary Learning
نویسندگان
چکیده
|This paper proposes a new neural architecture (Nessy) which uses evolutionary optimization for learning. The architecture, the outline of its evolutionary algorithm and the learning laws are given. Nessy is based on several modi cations of the multilayer backpropagation neural network. The neurons represent genes of evolutionary optimization, refered to as solutions. Weights represent probabilities and are used for selectioning. The training value of the output layer is set to Zero, the theoretical limit of every cost-oriented optimization, and the crossover operator is replaced by a transduction operator. Mutation is used as usual. Nessy algorithm can be characterized as individual evolutionary algorithm, but as a neural network too. It was designed for image processing applications. A short example is presented, where the discriminative feature of two images is succesfully detected by the proposed evolutionary neural network. Keywords|Neural Learning, Evolutionary Learning Neural Networks, Optimization, Image Processing.
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