Circuit implementation of digitally programmable transconductance amplifier in analog simulation of reaction-diffusion neural model

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• 作者：Miao Sun^aAuthor Vitae ; Xing He^a ; ^{hexingdoc@hotmail.com}Author Vitae ; Tiancai Wang^aAuthor Vitae ; Jie Tan^aAuthor Vitae ; Dawen Xia^bAuthor Vitae
• 关键词：Reaction-diffusion equation ; Neural network ; Circuit implementation
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：227
• 期：Complete
• 页码：74-81
• 全文大小：1500 K
• 卷排序：227

文摘

This paper is concerned with circuit implementation in reaction-diffusion neuron model. Firstly, in order to realize easily, one obtains the equivalent form by discretization of this neuron model. In the frame of discrete model, every parameter can be represented by the basic circuit component. Then the digital programmable transconductance amplifier (DPTA) is designed to realize the digitally function in circuit. In addition, the DPTA is applied to realize two activation functions and the simulation results are verified in Multisim.