Volume : VII, Issue : VIII, August - 2018

DESIGNING OF NEURAL NETWORK FOR SWITCHING NETWORK CONTROL

Santosh Kumar, Dr. R. K. Singh

Abstract :

A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/specification times; not guaranteed to work on all inputs; requires full connectivity.

Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits–generalizations of the Winner–Take–All circuit – that allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and non–neural. By exploiting regularities in our definition, we can construct efficient networks.

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Santosh Kumar, DR.R.K.SINGH, DESIGNING OF NEURAL NETWORK FOR SWITCHING NETWORK CONTROL, INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH : Volume-7 | Issue-8 | August-2018

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