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Abderrezak Guessoum
University Saad Dahlab Blida1
Computer Science & IT Electrical & Electronics Engineering

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A Novel Neuroglial Architecture for Modelling Singular Perturbation System Samia Salah; M'hamed Hadj Sadok; Abderrezak Guessoum
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (979.904 KB) | DOI: 10.11591/ijece.v8i6.pp4810-4822

Abstract

This work develops a new modular architecture that emulates a recently-discovered biological paradigm. It originates from the human brain where the information flows along two different pathways and is processed along two time scales: one is a fast neural network (NN) and the other is a slow network called the glial network (GN). It was found that the neural network is powered and controlled by the glial network. Based on our biological knowledge of glial cells and the powerful concept of modularity, a novel approach called artificial neuroglial Network (ANGN) was designed and an algorithm based on different concepts of modularity was also developed. The implementation is based on the notion of multi-time scale systems. Validation is performed through an asynchronous machine (ASM) modeled in the standard singularly perturbed form. We apply the geometrical approach, based on Gerschgorin’s circle theorem (GCT), to separate the fast and slow variables, as well as the singular perturbation method (SPM) to determine the reduced models. This new architecture makes it possible to obtain smaller networks with less complexity and better performance.
Co-Authors M'hamed Hadj Sadok Samia Salah