Multi-Layer Neuromorphic Synapse for Reconfigurable Networks

Amir Zjajo, Sumeet Kumar, Rene Van Leuken

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

In pulse-based neural networks, synaptic dynamics can have direct influence on learning of neural codes, and encoding of spatiotemporal spike patterns. In this paper, we propose an adaptive synapse circuit for increased flexibility and efficacy of signal processing units in neuromorphic structures. The synapse acts as a multi-layer computational network, and includes multi-compartment dendrites and different types of post-synaptic back propagating signals. With built-in temporal control mechanisms, the resulting reconfigurable network allows the implementation of synaptic homeostatics.

Original languageEnglish
Title of host publication2018 14th IEEE International Conference on Signal Processing (ICSP)
EditorsZhao Yao, An Gaoyun, Ruan Qiuqi, Yuan Baozong
Place of PublicationBeijing
PublisherIEEE
Pages997-1000
Number of pages4
ISBN (Electronic)978-1-5386-4673-1
ISBN (Print)978-1-5386-4674-8
DOIs
Publication statusPublished - 2019
Event14th IEEE International Conference on Signal Processing, ICSP 2018 - Beijing, China
Duration: 12 Aug 201816 Aug 2018

Conference

Conference14th IEEE International Conference on Signal Processing, ICSP 2018
CountryChina
CityBeijing
Period12/08/1816/08/18

Keywords

  • Cognitive systems
  • Neuromorphic circuits
  • Synapse

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