Evolutionary Discovery of Learning Rules for Feedforward Neural Networks with Step Activation Function
نویسندگان
چکیده
Neural networks with step activation function can be very efficient ways of performing non linear mappings. However, no standard learning algorithm exists for training this kind of neural networks. In this work we use Genetic Programming (GP) to discover supervised learning algorithms which can train neural networks with step activation function. Thanks to GP, a new learning algorithm has been discovered which has been shown to provide good performance.
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تاریخ انتشار 1999