基于FPGA的生物神经元智克维奇模型硬件实现模型的综合

A. Zhilenkov, Maria V. Kotlyarevskaya
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引用次数: 14

摘要

神经技术领域经过多年的研究和发展,产生了种类繁多的人工神经网络,这在一定程度上使人联想到生物神经系统的工作。本文考虑了脉冲神经网络的神经元。使用这种类型的神经网络的优先领域:空间导航和环境分析;气味分析和动态图形和声音信息;神经义肢和神经接口。在分析和估计了神经网络硬件实现中各种神经元模型的功能后,选择了Izhikevich模型。该模型具有生物学上的现实性,并且对计算资源的要求较低。考虑了神经元的数学模型和基于FPGA的硬件实现模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis of model of hardware realization of izhikevich model of biological neuron on the basis of FPGA
For years of researches and developments in the field of neurotechnologies a big variety of the artificial neural networks somewhat reminding work of biological neural systems was created. In article the neuron of spiking neural network is considered. Priority fields of use of neural networks of this type: spatial navigation and analysis of the environment; analysis of smells and dynamic graphic and sound information; neuroprosthetics and neurointerfaces. Having analysed and having estimated functionality of various models of neurons for hardware realization of neural network, Izhikevich's model was chosen. This model is biologically realistic and has the lowered requirements to computing resources. The mathematical model of neuron and model of its hardware realization on the basis of FPGA is considered.
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