Perceptron Learning Rule

Preliminaries An Introduction to Neural Networks Neuron Model and Network Architecture Perceptron Learning Rule Implement of Perceptron1 What we need to do next is to implement the algorithm described in ‘Perceptron Learning Rule’ and observe the effect of 1. different parameters, 2. different training sets, 3. and different transfer functions. A single neuron perceptron consists of a linear combination and a threshold operation simply. So we note its capacity is close to a linear classification....

Preliminaries supervised learning unsupervised learning reinforcement learning ‘An Introduction to Neural Networks’ Learning Rules1 We have built some neural network models in the post ‘An Introduction to Neural Networks’ and as we know architectures and learning rules are two main aspects of designing a useful network. The architectures we have introduced could not be used yet. What we are going to do is to investigate the learning rules for different architectures....