Multi-input silicon neuron with weighting adaptation

Ming Ze Li*, Ping Wang Po, Kea Tiong Tang, Wai-Chi  Fang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a biologically inspired "integrate-and-fire (I&F) neuron" which has multiple input dendrites for adaptive weight storage. By using a capacitor-free integrator, longer time constant and smaller chip area can be achieved. A low-power Schmitt Trigger is used to implement the feedback loop to achieve smaller power consumption. Weights are stored by using floating gate MOS transistors as nonvolatile analog memory. Simulation results show that this I&F neuron can be utilized in an analog VLSI neural network system.

Original languageEnglish
Title of host publication2009 IEEE/NIH Life Science Systems and Applications Workshop, LiSSA 2009
Pages194-197
Number of pages4
DOIs
StatePublished - 23 Jul 2009
Event2009 IEEE/NIH Life Science Systems and Applications Workshop, LiSSA 2009 - Bethesda, MD, United States
Duration: 9 Apr 200910 Apr 2009

Publication series

Name2009 IEEE/NIH Life Science Systems and Applications Workshop, LiSSA 2009

Conference

Conference2009 IEEE/NIH Life Science Systems and Applications Workshop, LiSSA 2009
CountryUnited States
CityBethesda, MD
Period9/04/0910/04/09

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