Computational Modeling with Spiking Neural Networks
作者： Stefan Schliebs , Nikola Kasabov
DOI: 10.1007/978-3-642-30574-0_37
关键词: Artificial intelligence 、 Encoding (memory) 、 Synaptic weight 、 Spiking neural network 、 Background information 、 Spike train 、 Types of artificial neural networks 、 Computer science 、 Field (computer science) 、 Classification methods
摘要: This chapter reviews recent developments in the area of spiking neural networks (SNN) and summarizes main contributions to this research field. We give background information about functioning biological neurons, discuss most important mathematical models along with encoding techniques, learning algorithms, applications neurons. As a specific application, evolving network (eSNN) classification method is presented detail principles numerous eSNN based are highlighted discussed.
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