AI Chat AI Image Generator AI Video Text to Speech

Supervised learning in Spiking Neural Networks with Limited Precision: SNN/LP

07/01/2014

∙

by Evangelos Stromatias, et al.

∙

∙

A new supervised learning algorithm, SNN/LP, is proposed for Spiking Neural Networks. This novel algorithm uses limited precision for both synaptic weights and synaptic delays; 3 bits in each case. Also a genetic algorithm is used for the supervised training. The results are comparable or better than previously published work. The results are applicable to the realization of large scale hardware neural networks. One of the trained networks is implemented in programmable hardware.

Evangelos Stromatias
2 publications
John Marsland
1 publication

page 1

page 2

page 3

page 4

research

∙ 09/13/2011

Developing a supervised training algorithm for limited precision feed-forward spiking neural networks

Spiking neural networks have been referred to as the third generation of...

0 Evangelos Stromatias, et al. ∙

research

∙ 11/24/2022

PC-SNN: Supervised Learning with Local Hebbian Synaptic Plasticity based on Predictive Coding in Spiking Neural Networks

Deemed as the third generation of neural networks, the event-driven Spik...

0 Mengting Lan, et al. ∙

research

∙ 06/09/2023

Beyond Weights: Deep learning in Spiking Neural Networks with pure synaptic-delay training

Biological evidence suggests that adaptation of synaptic delays on short...

0 Edoardo W. Grappolini, et al. ∙

research

∙ 01/14/2016

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding

Precise spike timing as a means to encode information in neural networks...

0 Brian Gardner, et al. ∙

research

∙ 02/12/2016

Learning may need only a few bits of synaptic precision

Learning in neural networks poses peculiar challenges when using discret...

0 Carlo Baldassi, et al. ∙

research

∙ 03/30/2021

Training Sparse Neural Network by Constraining Synaptic Weight on Unit Lp Sphere

Sparse deep neural networks have shown their advantages over dense model...

0 Weipeng Li, et al. ∙

research

∙ 08/31/2015

A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers

Learning Classifier Systems (LCS) are population-based reinforcement lea...

0 David Howard, et al. ∙