Neural networks approach v/s Algorithmic approach : A study through pattern recognition

Abstract

There is a great scope of expansion in the field of Neural Network, as it can be viewed as massively parallel computing systems consisting of an extremely large number of simple processors with many interconnections. NN models attempt to use some organizational principles in a weighted directed graphs in which nodes are artificial neurons and directed edges are connections between neuron outputs and neuron inputs. The main characteristic of neural network is that they have the ability to learn complex nonlinear input output relationships. A single artificial neuron is a simulation of a neuron (basic human brain cell) and scientists have tried to emulate the neuron in a form of artificial neuron called perceptron. Pattern recognition is one of the areas where the neural approach has been successfully tried. This study is concerned to see the journey of pattern recognition from algorithmic approach to neural network approach.