Supervised Learning in Multilayer Spiking Neural Networks

Details Supervised Learning in Multilayer Spiking Neural Networks Supervised Learning in Multilayer Spiking Neural Networks

2012-02-10

arxiv.org/abs/1202.2249v1

Computer Science

Neural and Evolutionary Computing

38 pages, 4 figures

Scientific paper

The current article introduces a supervised learning algorithm for multilayer spiking neural networks. The algorithm presented here overcomes some limitations of existing learning algorithms as it can be applied to neurons firing multiple spikes and it can in principle be applied to any linearisable neuron model. The algorithm is applied successfully to various benchmarks, such as the XOR problem and the Iris data set, as well as complex classifications problems. The simulations also show the flexibility of this supervised learning algorithm which permits different encodings of the spike timing patterns, including precise spike trains encoding.

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