Spatio-temporal Map Formation Based on a Potential Function

Gowgi, Prayag and Srinivasa, Shayan Garani (2015) Spatio-temporal Map Formation Based on a Potential Function. In: International Joint Conference on Neural Networks (IJCNN), JUL 12-17, 2015, Killarney, IRELAND.

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Abstract

We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.

Item Type:	Conference Proceedings
Series.:	IEEE International Joint Conference on Neural Networks (IJCNN)
Publisher:	IEEE
Additional Information:	Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre:	Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Date Deposited:	12 Apr 2016 06:26
Last Modified:	12 Apr 2016 06:26
URI:	http://eprints.iisc.ac.in/id/eprint/53663

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