Implementation of Feed Forward and Feedback Neural Network for Signal Processing Using Analog VLSI Technology

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Provided by: SSRG International Journals
Topic: Hardware
Format: PDF
Artificial intelligence through a biological world is realized based on mathematical equations and artificial neurons. Main focus is on the implementation of feedforward and feedback Neural Network Architecture (NNA) with on a chip learning in analog VLSI for generic signal processing applications. In the proposed paper analog components like Gilbert Cell Multiplier (GCM), Neuron Activation Function (NAF) is used to implement artificial feedforward and feedback NNA. The analog components used are comprises of multipliers and adders' along with the tan-sigmoid function circuit using MOS transistor in sub threshold region.
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