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研究生: 楊斯閔
Yang Ssu-Min
論文名稱: Kernel-Based Fuzzy c-Means分群演算法 硬體架構實現
Kernel-Based Fuzzy c-Means Clustering Algorithm Hadrware Implementation
指導教授: 黃文吉
Hwang, Wen-Jyi
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2011
畢業學年度: 99
語文別: 中文
論文頁數: 49
中文關鍵詞: 可程式邏輯陣列FCM演算法系統程式晶片設計KFCM演算法
論文種類: 學術論文
相關次數: 點閱:156下載:12
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  • 本論文根據文獻[6],以其FCM分群演算法的硬體架構為基礎,實作以非線性高斯核函式為核距離計算之KFCM分群演算法硬體電路,具有管線化以及可以同時計算所有分群之權重係數的能力。此架構改良了以往FCM分群演算法對於非線性資料分群效果不佳的問題,並且能夠應用在帶有雜訊的資料。本論文使用FPGA實現我們提出的硬體架構,並使用Iris data與人工雜訊圖片作為實驗測詴資料。實驗結果顯示本架構對於非線性資料分群效果確實較FCM佳,且架構簡單提供了日後高度的延伸性。

    中文摘要 .....................................i 誌謝 .........................................ii 目 錄 ........................................iii 附表目錄 .....................................v 附圖目錄 .....................................vi 第一章 緒論 ..................................1 1.1 研究背景 .................................1 1.2 研究動機與目的 ...........................4 1.3 全文架構 .................................5 第二章 理論基礎與技術背景 ....................7 2.1 Kernel-Based Fuzzy C-Means演算法 .........7 2.2 SOPC 系統整合設計 ........................11 第三章 基礎電路架構介紹 ......................14 3.1 KFCM .....................................14 3.1.1 Pre-computation unit ...................15 3.1.2 Membership Coefficients Updating Unit ..19 3.1.3 Centroid updating unit .................22 3.1.4 Cost function computation unit .........24 第四章 實驗結果與數據探討 ....................26 4.1 開發平台與實驗環境介紹 ...................26 4.2 實驗數據的呈現與討論 .....................29 4.2.1 Iris Data Set分群結果比較 ..............29 4.2.2 加入人工雜訊之圖片分群結果 .............34 第五章 結論 ..................................47 參考著作 .....................................48

    [1]Bezdek, J. C., "Fuzzy mathematics in pattern classification," Ph.D. dissertation,
    Cornell Univ., Ithaca, NY, 1973.
    [2] S.Chen, D.Zhang, "Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics , vol.34, no.4, pp.1907-1916, Aug. 2004.
    [3]J. Garcia-Lamont, L.M. Flores-Nava, F. Gomez-Castaneda, J.A. Moreno-Cadenas,
    "CMOS Analog Circuit for Fuzzy C-Means Clustering," IEEE Proc. 5th
    Biannual World Automation Congress, 2002.
    [4] P. Hung, H. Fahmy, O. Mencer, and M. J. Flynn, "Fast Division Algorithm with a Small Lookup Table," IEEE Asilomar Conference on Signals, Systems, and Computers, pp.1465-1468, 1999.
    [5] J.F. Kolen and T. Hutcheson, "Reducing the Time Complexity of the Fuzzy C-Means Algorithm," IEEE Trans. Fuzzy Systems, pp. 263-267, Vol. 10, 2002.
    [6] Hui-Ya Li, Cheng-Tsun Yang, Wen-Jyi Hwang, “Efficient VLSI Architecture for Fuzzy C-Means Clustering in Reconfigurable Hardware”, Proc. IEEE International conference on Frontier of Computer Science and Technology, 2009, p.168-174.
    [7] Ben Chaabane, S.; Sayadi, M.; Fnaiech, F.; Brassart, E.; , "Color image segmentation using automatic thresholding and the fuzzy C-means techniques," The 14th IEEE Mediterranean Electrotechnical Conference, vol., no., pp.857-861, 5-7 May 2008.
    [8] R.A. Fisher “Iris Data Set” 1936 http://archive.ics.uci.edu/ml/datasets/Iris.
    [9] Hathaway, R.J.; Bezdek, J.C.;, "Fuzzy c-means clustering of incomplete data," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol.31, no.5, pp.735-744, Oct 2001.
    [10] 張嘉晏, “以Fuzzy C-Means硬體架構為基礎之快速影像分割之研究,” 碩士論文, 國立臺灣師範大學資訊工程學系, 民國九十九年
    [11] 楊正存, “在可程式化系統晶片上之Fuzzy C-Means分群演算法設計”, 碩士論文, 國立臺灣師範大學資訊工程學系, 民國九十八年
    [12] Nios II Processor Reference Handbook, 2011, Altera Corporation, http://www.altera.com/literature/hb/nios2/n2cpu_nii5v1.pdf.
    [13] SOPC Builder User Guide, 2010, Altera Corporation, http://www.altera.com/literature/ug/ug_sopc_builder.pdf.
    [14] Hyun-Chul Kim , Daijin Kim , Sung Yang Bang, A numeral character recognition using the PCA Mixture model, Pattern Recognition Letters, v.23 n.1-3, p.103-111, January 2002.
    [15] Xiaowei Yang; Guangquan Zhang; Jie Lu; Jun Ma; , "A Kernel Fuzzy c-Means Clustering-Based Fuzzy Support Vector Machine Algorithm for Classification Problems With Outliers or Noises," IEEE Transactions on Fuzzy Systems, vol.19, no.1, pp.105-115, Feb. 2011.
    [16] Kanzawa, Y.; Endo, Y.; Miyamoto, S.; , "On kernel fuzzy c-means for data with tolerance using explicit mapping for kernel data analysis," 2010 IEEE International Conference on Fuzzy Systems (FUZZ), vol., no., pp.1-6, 18-23, July 2010.
    [17] Long Chen; Mingzhu Lu; Chen, C.L.P.;, "Multiple kernel fuzzy C-means based image segmentation," 2010 IEEE International Conference on Systems Man and Cybernetics (SMC), vol., no., pp.4123-4129, 10-13, Oct. 2010.

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