SoPC-based C-Means Clustering Algorithm Design

碩士 === 國立臺灣師範大學 === 資訊工程研究所 === 96 === A novel hardware architecture for c-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. A simple divider...

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Main Authors: Chih Chieh Hsu, 許智傑
Other Authors: Wen-Jyi Hwang
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/43599076019067384097
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spelling ndltd-TW-096NTNU53920092015-10-13T13:08:49Z http://ndltd.ncl.edu.tw/handle/43599076019067384097 SoPC-based C-Means Clustering Algorithm Design 在可程式化系統晶片上之C-Means分群演算法設計 Chih Chieh Hsu 許智傑 碩士 國立臺灣師範大學 資訊工程研究所 96 A novel hardware architecture for c-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. A simple divider circuit based on table lookup, multiplication and shift operations is employed for reducing both the area cost and latency for centroid computation. 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 hardware complexity and high computation performance for c-means design. Wen-Jyi Hwang 黃文吉 2008 學位論文 ; thesis 43 zh-TW
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description 碩士 === 國立臺灣師範大學 === 資訊工程研究所 === 96 === A novel hardware architecture for c-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. A simple divider circuit based on table lookup, multiplication and shift operations is employed for reducing both the area cost and latency for centroid computation. 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 hardware complexity and high computation performance for c-means design.
author2 Wen-Jyi Hwang
author_facet Wen-Jyi Hwang
Chih Chieh Hsu
許智傑
author Chih Chieh Hsu
許智傑
spellingShingle Chih Chieh Hsu
許智傑
SoPC-based C-Means Clustering Algorithm Design
author_sort Chih Chieh Hsu
title SoPC-based C-Means Clustering Algorithm Design
title_short SoPC-based C-Means Clustering Algorithm Design
title_full SoPC-based C-Means Clustering Algorithm Design
title_fullStr SoPC-based C-Means Clustering Algorithm Design
title_full_unstemmed SoPC-based C-Means Clustering Algorithm Design
title_sort sopc-based c-means clustering algorithm design
publishDate 2008
url http://ndltd.ncl.edu.tw/handle/43599076019067384097
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