English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 51275/86342 (59%)
造訪人次 : 8147014      線上人數 : 57
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/82991

    題名: Image Reconstruction of a Buried Conductor by Modified Particle Swarm Optimization
    作者: Chiu, Chien-Ching;Chen, Chien-Hung;Fan, Yu-Sheng
    貢獻者: 淡江大學電機工程學系
    關鍵詞: IMAGE reconstruction;SWARM intelligence;ALGORITHMS;MATHEMATICAL optimization;NONLINEAR theories
    日期: 2012-07
    上傳時間: 2013-03-13 02:57:05 (UTC+8)
    出版者: Medknow Publications and Media Pvt. Ltd.
    摘要: In this paper, the shape reconstruction of a perfectly conducting cylinder buried in a half-space by measured transverse magnetic scattered field and the modified particle swarm optimization (MPSO). Assume that a conducting cylinder of unknown shape is buried in one half-space and scatters the field incident from another half-space where the scattered filed is measured. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. The inverse problem is resolved by an optimization approach, and the global searching scheme PSO is then employed to search the parameter space. Two algorithms: the PSO and the MPSO have been examined. Both techniques have been tested in the case of simulated measurements contaminated by additive Gaussian noise. Numerical results demonstrate that even when the initial guess is far away from the exact one, the two algorithms can both obtain good reconstruction and the MPSO outperforms the PSO in convergence speed.
    關聯: IETE Journal of Research 58(4), pp.284-291
    DOI: 10.4103/0377-2063.102307
    顯示於類別:[電機工程學系暨研究所] 期刊論文


    檔案 描述 大小格式瀏覽次數
    0974-780X_58(4)p284-291.pdf757KbAdobe PDF156檢視/開啟



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋