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N. Balaji, Dr.
- VLSI Implementation of the High Speed Spiking Neural Network for Pattern Recognition with Modified LIF Neuron .
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1 no, IN
1 no, IN
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Artificial Intelligent Systems and Machine Learning, Vol 13, No 2 (2021), Pagination: 26 - 34Abstract
-For Biomedical application, analysis of data through modern computational methodologies is required. Machine learning based architectures enhance the way that the diagnosis is performed. The objective of the research work is to design a Neuromorphic system using nano-electronics and Artificial Intelligence for feature extraction and classification of medical data. The research area is a combination of nano-electronics, computer technology, and biology. This paper presents the multiplier less Modified Leaky Integrate and Fire Neuron Unit (MLIFNU) and proposed a modified Spiking Neural Network(SNN) architecture for Pattern Recognition application. Synthesis results of implementation on fieldprogrammable gate array are presented. Accordingly, the maximum frequency of the MLIFNU and SNN are 361.991 MHz and 281.442 MHz, respectively.Keywords
Spiking Neural Network (SNN), Artificial Intelligence, Neuromorphic system, Modified Leaky Inteegrate and Fire Neuron Unit (MLIFNU).
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