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Publication Type : Conference Paper
Thematic Areas : Learning-Technologies, Medical Sciences, Biotech
Publisher : Proceedings of the Fourth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Kochi, India
Source : Proceedings of the Fourth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Kochi, India (2015)
Campus : Amritapuri
School : School of Biotechnology
Center : Computational Neuroscience and Neurophysiology, Amrita Mind Brain Center, Biotechnology
Department : Computational Neuroscience Laboratory, biotechnology
Year : 2015
Abstract : Spiking neural encoding models allow classification of real world tasks to suit for brain-machine interfaces in addition to serving as internal models. We developed a new spike encoding model inspired from cerebellum granular layer and tested different classification techniques like SVM, Naïve Bayes, MLP for training spiking neural networks to perform pattern recognition tasks on encoded datasets. As a precursor to spiking network-based pattern recognition, in this study, real world datasets were encoded into spike trains. The objective of this study was to encode information from datasets into spiking neuron patterns that were relevant for spiking neural networks and for conventional machine learning algorithms. In this initial study, we present a new approach similar to cerebellum granular layer encoding and compared it with BSA encoding techniques. We have also compared the efficiency of the encoded dataset with different datasets and with standard machine learning algorithms. © 2015 IEEE.
Cite this Research Publication : Chaitanya Medini, Asha Vijayan, Ritu Maria Zacharia, Lekshmi Priya Rajagopal, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Spike Encoding for Pattern Recognition: Comparing Cerebellum Granular Layer Encoding and BSA algorithms”, in Proceedings of the Fourth International Conference on Advances in Computing, Communications and Informatics (ICACCI-2015), Aug 10-13, 2015, Kochi, India.