EVOLUTIONARY DESIGN OF SPIKING NEURAL NETWORKS

DOI10.1142/S179300570600049XzbMath1169.68570MaRDI QIDQ3421875

L. P. Maguire, Ammar Belatreche, Martin McGinnity, Qingxiang Wu

Publication date: 8 February 2007

Published in: New Mathematics and Natural Computation (Search for Journal in Brave)

zbMATH Keywords

supervised learningspiking neuronstemporal codingevolutionary strategiesaction potentialsspike response modelpostsynaptic potential

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

The maximum points-based supervised learning rule for spiking neural networks

Cites Work

• Mathematical formulations of Hebbian learning
• Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning
• Multisurface method of pattern separation for medical diagnosis applied to breast cytology.
• Spiking Neuron Models
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