VLSI FOR NEURAL NETWORKS AND THEIR APPLICATIONS

Jun 21st, 2015
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Alabama State University
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Most of the students of Electronics Engineering are exposed to Integrated Circuits (IC's) at a very basic level, involving SSI (small scale integration) circuits like logic gates or MSI (medium scale integration) circuits like multiplexers, parity encoders etc. But there is a lot bigger world out there involving miniaturization at levels so great, that a micrometer and a microsecond are literally considered huge! This is the world of VLSI - Very Large Scale Integration.

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VLSI FOR NEURAL NETWORKS AND THEIR APPLICATIONSABSTRACT : Most of the students of Electronics Engineering are exposed to Integrated Circuits (IC's) at a very basic level, involving SSI (small scale integration) circuits like logic gates or MSI (medium scale integration) circuits like multiplexers, parity encoders etc. But there is a lot bigger world out there involving miniaturization at levels so great, that a micrometer and a microsecond are literally considered huge! This is the world of VLSI - Very Large Scale Integration. Neural networks are a new method of programming computers. They are exceptionally good at performing pattern recognition and other tasks that are very difficult to program using conventional techniques. Programs that employ neural nets are also capable of learning on their own and adapting to changing conditions. Neural nets may be the future of computing .A good way to understand them is with a puzzle that neural nets can be used to solve. Suppose that you are given 500 characters of code that you know to be C, C++, Java, or Python. Now, construct a program that identifies the code's language. One solution is to construct a neural net that learns to identify these languages. According to a simplified account, the human brain consists of about ten

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