Temporal Sequence Learning in Spiking Neural Networks

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Title

Temporal Sequence Learning in Spiking Neural Networks

Content partner

Auckland University of Technology

Collection

Tuwhera

Description

Spiking Neural Networks (SNN) are the third generation of artificial neural network (ANN). Like the brain’s neurons, they use spikes (pulses) to propagate information. Spike sequence learning has many applications for example in speech recognition and motor control. One of the main issues for sequence generation is learning. There are two main types of learning, unsupervised learning and supervised learning. Supervised learning, like Back Propagation (BP) is based on using a teacher signal to...

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Format

Research paper

Research format

Thesis

Thesis level

Masters

Date created

2011

Creator

Mandurah, Belal

URL

https://openrepository.aut.ac.nz/handle/10292/4045

Related subjects

Spiking Neural Networks / Supervised Learning Algorithms / Dynamic Synapses / Static Synapses / Particle Swarm Optimization / Integrate and Fire Neuron models / Spike Pattern Association Neuron / Sequence Learning / Similarity Measure / Fitness function / Spatial temporal pattern recognition / Temporal Sequence Learning

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