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FPGA Implementation of Bio-Inspired Computing Architecture Based on Simple Neuron Model


3D Reconstruction in Canonical
Abstract


The processor architecture families are under power, thermal, and area constraints and considers allowing optimization of chip throughput for a specific device technology by an appropriate model for performance, memory sub-systems and interconnects for various technology architectures. The system level design framework provides the best possible design tradeoff for different technology and choice of processor architectures. The aim of Bio-Inspired engineering is to reverse engineer the human brain using VLSI as well as analog electronics circuits. This research manuscript depicts the demonstration of braininspired computing architecture based on Leaky-Integrate-and- File (LIF) neuron model for neuromorphic computing system is implemented on the Field Programmable Gate Array (FPGA). The reconfigurable and event driven parameters are considered to design a field-programmable neuromorphic computing system. The register transfer logic (RTL) results of implementation and hardware synthesis are presented as a proof of concept. The neuron model is explored in Xilinx-ISE software with utilizing Verilog code, considering digital implementation, aiming at highspeed low-cost large-scale systems.

KeyWords
Neuromorphic Computing, Processor Architecture, Neuron, Synapse, FPGA.



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