DEVELOPMENT AND SIMULATION OF SPIKE NEURAL NETWORK ARCHITECTURE

Abstract

A review of different models of spike neural networks has been conducted. A spike type neural network is developed in the article. The mathematical model of exchange of neurotransmitters between neurons is proposed. An algorithm for network operation and neuron interaction is proposed, as well as an approach to training the network based on the formation of new connections from dendrites and increasing the signal transmission coefficient. The model of neural network was created in Python using the developed algorithm and mathematical model. To speed up the calculations, they were paralleled using the Numba library. The library Matplotlib was used for visual modelling and plotting the number of neurotransmitters on neurons. Experimental studies of the developed model of biological type network were carried out. It was shown that the developed network after training responds faster to the signals that were applied to it in the process of training.

Recommended articles

COMPARISON OF THE EFFECTS OF STANDARD NOZZLES AND EXTENSION TUBES ON THE EROSION OF PMMA USING PULSATING WATER JET TECHNOLOGY

Gabriel Stolarik, Sergej Hloch, Akash Nag
Keywords: pulsating water jet | bone-cement disintegration | Extension tube nozzle

COMPARISON OF CHOSEN METAHEURISTIC ALGORITHMS FOR THE OPTIMIZATION OF THE ABRASIVE WATER JET TREATMENT PROCESS

M. Krakowiak, E. Kawecka, J. Podhajecki, A. Radomska-Zalas, A. Nag, A. Perec
Keywords: meta-heuristic algorithms; ALO; GWO; MFO | Abrasive Water Jet; AWJ