Review: Implementation of Feedforward and Feedback Neural Network for Signal Processing Using Analog VLSI Technology

摘要

Main focus of project is on implementation of Neural Network Architecture (NNA) with on chip learning on Analog VLSI Technology for signal processing application. In the proposed paper the analog components like Gilbert Cell Multiplier (GCM), Neuron Activation Function (NAF) are used to implement artificial NNA. Analog components used comprises of multiplier, adder and tan sigmoidal function circuit using MOS transistor. This Neural Architecture is trained using Back Propagation (BP) Algorithm in analog domain with new techniques of weight storage. Layout design and verification of above design is carried out using VLSI Backend Microwind 3.1 software Tool. The technology used to design layout is 32 nm CMOS Technology.