{"title":"自适应瞬态同步的神经突触计算元素:生物物理精度与硬件复杂性","authors":"A. Zjajo","doi":"10.1109/IWCIA47330.2019.8955105","DOIUrl":null,"url":null,"abstract":"In this paper, we examine electro-chemically accurate, multi-compartment, neurosynaptic computational elements, and analyze their complexity, accuracy, and flexibility in signal processing of a time-varying task. We evaluate distributed patterns of simultaneously firing neurons in space and time, and we establish a transient synchrony and homeostatic regulation mechanism upon the underlying synaptic connectivity. With synchronic spiking, we form synchronous groups of neuronal subpopulations, which represent content forming a coherent entity. The neurosynaptic computational elements implemented on Xilinx Virtex 7 XC7VX550 FPGA board illustrate feasibility of the methodology.","PeriodicalId":139434,"journal":{"name":"2019 IEEE 11th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neurosynaptic Computational Elements for Adaptive Transient Synchrony: Biophysical Accuracy versus Hardware Complexity\",\"authors\":\"A. Zjajo\",\"doi\":\"10.1109/IWCIA47330.2019.8955105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we examine electro-chemically accurate, multi-compartment, neurosynaptic computational elements, and analyze their complexity, accuracy, and flexibility in signal processing of a time-varying task. We evaluate distributed patterns of simultaneously firing neurons in space and time, and we establish a transient synchrony and homeostatic regulation mechanism upon the underlying synaptic connectivity. With synchronic spiking, we form synchronous groups of neuronal subpopulations, which represent content forming a coherent entity. The neurosynaptic computational elements implemented on Xilinx Virtex 7 XC7VX550 FPGA board illustrate feasibility of the methodology.\",\"PeriodicalId\":139434,\"journal\":{\"name\":\"2019 IEEE 11th International Workshop on Computational Intelligence and Applications (IWCIA)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 11th International Workshop on Computational Intelligence and Applications (IWCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWCIA47330.2019.8955105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 11th International Workshop on Computational Intelligence and Applications (IWCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWCIA47330.2019.8955105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neurosynaptic Computational Elements for Adaptive Transient Synchrony: Biophysical Accuracy versus Hardware Complexity
In this paper, we examine electro-chemically accurate, multi-compartment, neurosynaptic computational elements, and analyze their complexity, accuracy, and flexibility in signal processing of a time-varying task. We evaluate distributed patterns of simultaneously firing neurons in space and time, and we establish a transient synchrony and homeostatic regulation mechanism upon the underlying synaptic connectivity. With synchronic spiking, we form synchronous groups of neuronal subpopulations, which represent content forming a coherent entity. The neurosynaptic computational elements implemented on Xilinx Virtex 7 XC7VX550 FPGA board illustrate feasibility of the methodology.