@inproceedings{bd9e84296b694903b2c8a431821ba2a5,
title = "Efficient K-means VLSI architecture for vector quantization",
abstract = "A novel hardware architecture for k-means clustering is presented in this paper. Our architecture is fully pipelined for both the partitioning and centroid computation operations so that multiple training vectors can be concurrently processed. The proposed architecture is used as a hardware accelerator for a softcore NIOS CPU implemented on a FPGA device for physical performance measurement. Numerical results reveal that our design is an effective solution with low area cost and high computation performance for k-means design.",
author = "Li, {Hui Ya} and Hwang, {Wen Jyi} and Hsu, {Chih Chieh} and Hung, {Chia Lung}",
year = "2009",
doi = "10.1007/978-3-642-02230-2_45",
language = "English",
isbn = "3642022294",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "440--449",
booktitle = "Image Analysis - 16th Scandinavian Conference, SCIA 2009, Proceedings",
note = "16th Scandinavian Conference on Image Analysis, SCIA 2009 ; Conference date: 15-06-2009 Through 18-06-2009",
}