Implementation of Single Layer Perceptron Model using MATLAB

Abstract

ANN consists of hundreds of single units, artificial neurons or processing elements . Neurons are connected with weights, which constitute the neural structure and are organized in layers. Perceptron is single layer artificial neuron network and it works with continuous or binary inputs. In the modern sense perceptron is an algorithm for learning a binary classifier. In ANN the inputs are applied via series of weights and Actual output are compared to the target outputs. Then to adjust the weihts, learning rule is used and bias the network so that actual output move closer to the target output .The perceptron learning rules comes under the category of supervised learning. In this Paper , implementation of single layer perceptron model using single perceptron learning rule through MAT LAB is discussed.