ASIC Oriented Comparative Analysis Of Biologically Inspired Neuron Models
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Online Publication Date2019-02-28
Print Publication Date2018-08
Permanent link to this recordhttp://hdl.handle.net/10754/652977
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AbstractThis paper introduces the hardware and the ASIC implementations of the four most popular biologically inspired neuron models. The models are quartic, Izhikevich, Hindmarsh Rose and Fitzhugh-Nagumo. Moreover, some approximate computing techniques are applied on these models to reduce the area and power consumption. In addition, ASIC implementations of these models and their approximate versions are carried out. Also, spiking behavior error between these models and the Hodgkin Huxley model, the reference accurate model, is presented. Finally, a fair comparative analysis is discussed to help the Spiking Neural Networks designers to select the best neuron model hardware implementation from the power, area and accuracy perspectives.
CitationEl-Maksoud AJA, Elmasry YO, Salama KN, Mostafa H (2018) ASIC Oriented Comparative Analysis Of Biologically Inspired Neuron Models. 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS). Available: http://dx.doi.org/10.1109/MWSCAS.2018.8623858.
SponsorsThis research was partially funded by ONE Lab at Cairo University, Zewail City of Science and Technology, and KAUST.
Conference/Event name61st IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2018