Study of Аlgorithms for Spiking Neural Networks Supervised Training

Student: Vdovina Evgeniya

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Mathematical Methods of Modelling and Computer Technologies (Master)

Year of Graduation: 2018

The third generation of neural networks, impulse (or spike) neural networks, is the most biologically realistic model of artificial neural networks. it is little known, and has not yet come up with a perfect algorithm for its training, but it is an attractive object of research, as it has a huge number of advantages compared to previous generations. The paper studies the implementation of a spike neural network and its training by the method of back propagation of the error. During the execution, a lot of tests were carried out, it was shown that a slight change in the input parameters led to significant changes in the resulting data, an assessment of the prospects of the tested library and suggestions for improving the results was given.

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