Hardware implementation of κ-winner-take-all neural network with on-chip learning

Hui Ya Li, Chien Min Ou, Yi Tsan Hung, Wen Jyi Hwang, Chia Lung Hung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper presents a novel pipelined architecture of the competitive learning (CL) algorithm with κ-winners-take-all activation. The architecture employs a codeword swapping scheme so that neurons failing the competition for a training vector are immediately available for the competitions for the subsequent training vectors. An efficient pipeline architecture is then designed based on the codeword swapping scheme for enhancing the throughput. The CPU time of the NIOS processor executing the CL training with the proposed architecture as an accelerator is measured. Experiment results show that the CPU time is lower than that of other hardware or software implementations running the CL training program with or without the support of custom hardware.

Original languageEnglish
Title of host publicationProceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010
Pages340-345
Number of pages6
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010 - Hong Kong, China
Duration: 2010 Dec 112010 Dec 13

Publication series

NameProceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010

Other

Other2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010
CountryChina
CityHong Kong
Period10/12/1110/12/13

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Keywords

  • Competitive learning
  • FPGA
  • On-chip learning
  • Reconfigurable computing
  • κ-winners-take-all

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

Cite this

Li, H. Y., Ou, C. M., Hung, Y. T., Hwang, W. J., & Hung, C. L. (2010). Hardware implementation of κ-winner-take-all neural network with on-chip learning. In Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010 (pp. 340-345). [5692497] (Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010). https://doi.org/10.1109/CSE.2010.51