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All Journal International Journal of Electrical and Computer Engineering
Paeen Afrakoti, Iman Esmaili
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Computer Science & IT Electrical & Electronics Engineering

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Spiking ink drop spread clustering algorithm and its memristor crossbar conceptual hardware design Paeen Afrakoti, Iman Esmaili; Nazerian, Vahdat; Sutikno, Tole
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp7125-7136

Abstract

In this study, a novel neuro-fuzzy clustering algorithm is proposed based on spiking neural network and ink drop spread (IDS) concepts. The proposed structure is a one-layer artificial neural network with leaky integrate and fire (LIF) neurons. The structure implements the IDS algorithm as a fuzzy concept. Each training data will result in firing the corresponding input neuron and its neighboring neurons. A synchronous time coding algorithm is used to manage input and output neurons firing time. For an input data, one or several output neurons of the network will fire; confidence degree of the network to outputs is defined as the relative delay of the firing times with respect to the synchronous pulse. A memristor crossbar-based hardware is utilized for hardware implementation of the proposed algorithm. The simulation result corroborates that the proposed algorithm can be used as a neuro-fuzzy clustering and vector quantization algorithm.
Co-Authors Nazerian, Vahdat Tole Sutikno