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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
