Performance Learning

Preliminaries ‘Performance Surfaces and Optimum Points’ Linear algebra stochastic approximation Probability Theory ADALINE, LMS, and Widrow-Hoff learning1 Performance learning had been discussed. But we have not used it in any neural network. In this post, we talk about an important application of performance learning. And this new neural network was invented by Frank Widrow and his graduate student Marcian Hoff in 1960. It was almost the same time as Perceptron was developed which had been discussed in ‘Perceptron Learning Rule’....

Preliminaries Perceptron learning algorithm Hebbian learning algorithm Linear algebra Neural Network Training Technique1 Several architectures of the neural networks had been introduced. And each neural network had its own learning rule, like, the perceptron learning algorithm, and the Hebbian learning algorithm. When more and more neural network architectures were designed, some general training methods were necessary. Up to now, we can classify all training rules in three categories in a general way:...