A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
A randomized algorithm for estimating the number of clusters
Automation and Remote Control
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A new stochastic approximation algorithm with input perturbation for self-learning is designed with test perturbations and has certain useful properties, such as consistency of estimates under almost arbitrary perturbations and preservation of simplicity and performance with the growing size of the state space and increasing number of classes. An example on computer-aided modeling of learning is given to illustrate the performance of the algorithm.