Fast fuzzy c-means clustering based on low-cost high-performance VLSI architecture in reconfigurable hardware

Yao Jung Yeh, Hui Ya Li, Cheng Yen Yang, Wen Jyi Hwang

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

1 Citation (Scopus)

Abstract

This paper presents a novel low-cost and high-performance VLSI architecture for fuzzy c-means clustering. In the architecture, the operations at both the centroid and data levels are pipelined to attain high computational speed while consuming low hardware resources. In addition, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. Experimental results show that the proposed solution is an effective alternative for cluster analysis with low computational cost and high performance.

Original languageEnglish
Title of host publicationProceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010
Pages112-118
Number of pages7
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

Fingerprint

Reconfigurable hardware
Cluster analysis
Costs
Hardware

Keywords

  • Data clustering
  • FPGA
  • Fuzzy c-means
  • Fuzzy system
  • Reconfigurable computing
  • System on programmable chip

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

Cite this

Yeh, Y. J., Li, H. Y., Yang, C. Y., & Hwang, W. J. (2010). Fast fuzzy c-means clustering based on low-cost high-performance VLSI architecture in reconfigurable hardware. In Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010 (pp. 112-118). [5692464] (Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010). https://doi.org/10.1109/CSE.2010.22

Fast fuzzy c-means clustering based on low-cost high-performance VLSI architecture in reconfigurable hardware. / Yeh, Yao Jung; Li, Hui Ya; Yang, Cheng Yen; Hwang, Wen Jyi.

Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010. 2010. p. 112-118 5692464 (Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010).

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

Yeh, YJ, Li, HY, Yang, CY & Hwang, WJ 2010, Fast fuzzy c-means clustering based on low-cost high-performance VLSI architecture in reconfigurable hardware. in Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010., 5692464, Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010, pp. 112-118, 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010, Hong Kong, China, 10/12/11. https://doi.org/10.1109/CSE.2010.22
Yeh YJ, Li HY, Yang CY, Hwang WJ. Fast fuzzy c-means clustering based on low-cost high-performance VLSI architecture in reconfigurable hardware. In Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010. 2010. p. 112-118. 5692464. (Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010). https://doi.org/10.1109/CSE.2010.22
Yeh, Yao Jung ; Li, Hui Ya ; Yang, Cheng Yen ; Hwang, Wen Jyi. / Fast fuzzy c-means clustering based on low-cost high-performance VLSI architecture in reconfigurable hardware. Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010. 2010. pp. 112-118 (Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010).
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