Multi-Layer Neuromorphic Synapse for Reconfigurable Networks

Conference Paper (2019)
Author(s)

Amir Zjajjo (TU Delft - Signal Processing Systems)

Sumeet Kumar (TU Delft - Signal Processing Systems)

T.G.R.M. Leuken (TU Delft - Signal Processing Systems)

Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.1109/ICSP.2018.8652360
More Info
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Publication Year
2019
Language
English
Research Group
Signal Processing Systems
Pages (from-to)
997-1000
ISBN (print)
978-1-5386-4674-8
ISBN (electronic)
978-1-5386-4673-1

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.

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