Rough winner-take-all for hardware oriented vector quantization algorithm

IEICE Electronics Express

Keiichi Horio¹  Masatoshi Sekine²  Hakaru Tamukoh²  Takeshi Yamakawa¹ 

[1] Graduate School of Life Science and System Engineering, Kyushu Institute of Technology;Institute of Engineering, Tokyo University of Agriculture and Technology

关键词: vector quantization;    rough-winner-take-all;    WTA;    k-means;    neural gas;    self-organizing map;    digital hardware;   

DOI  :  10.1587/elex.8.773

学科分类：电子、光学、磁材料

来源: Denshi Jouhou Tsuushin Gakkai

【 摘 要 】

References(6)In this paper, we propose a hardware oriented vector quantization algorithm employing rough-winner-take-all neural network. The proposed algorithm is almost same as K-means clustering which is the simplest vector quantization. The only different point is that the proposed method employs rough-winner-take-all as the substitute of ordinary winner-take-all. In a rough-winner-take-all strategy, the winner is roughly selected in the early learning stage and is strictly assigned in the later stage. The simulation results show that the quantization performance of the proposed method is nearly equal to Neural Gas which is an excellent vector quantization. Besides, the proposed method can be realized as an extra mode of existing K-means or Self-Organizing Map hardware by changing its winner-take-all controlling.

【 授权许可】

Unknown