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• W4306732047 startingPage "1366" @default.
• W4306732047 abstract "Digital realization of neuron models, especially implementation on a field programmable gate array (FPGA), is one of the key objectives of neuromorphic research, because the effective hardware realization of the biological neural networks plays a crucial role in implementing the behaviors of the brain for future applications. In this paper, a hybrid FitzHugh Nagumo-Morris Lecar (FNML) neuron model with electromagnetic flux coupling is considered, and two multiplierless piecewise linear (PWL) models, which have similar behaviors to the biological neuron, are presented. A comparison between digital implementation results of the original FNML and PWL models illustrates that, the PWL1 model provides a 65% speed-up with an overall saving (in FPGA resources) of 66.2%, and the PWL2 model yields a 71% speed-up with an overall saving of 78.2%." @default.
• W4306732047 created "2022-10-19" @default.
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• W4306732047 date "2022-12-01" @default.
• W4306732047 modified "2023-10-17" @default.
• W4306732047 title "Low Cost Digital Implementation of Hybrid FitzHugh Nagumo–Morris Lecar Neuron Model Considering Electromagnetic Flux Coupling" @default.
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• W4306732047 doi "https://doi.org/10.1109/tbcas.2022.3214851" @default.
• W4306732047 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36251896" @default.
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