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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/88100

    Title: 使用隨機式最佳化法於二維散射體之逆散射研究
    Other Titles: Application of stochastic optimization methods to the inverse scattering of 2-D scatterers
    Authors: 孫積賢;Sun, Chi-Hsien
    Contributors: 淡江大學電機工程學系博士班
    丘建青;Chiu, Chien Ching
    Keywords: 逆散射;微波成像;時域有限差分法;演化計算;Inverse scattering;Finite Difference Time Domain (FDTD);Moment Method (MoM);Green’s Function;Dynamic Differential Evolution (DDE);Self-Adaptive Dynamic Differential Evolution (SADDE);Particle Swarm Optimization (PSO);Asynchronous Particle Swarm Optimization (APSO)
    Date: 2012
    Issue Date: 2013-04-13 12:00:43 (UTC+8)
    Abstract: 本論文提出一種新型隨機式最佳化演算法應用於高維度測試函數與二維逆散射問題。本論文的貢獻有兩點,第一點將隨機式最佳化演算法在九種不同特性之測試函數進行測試,結果發現,將”最佳”概念引進隨機式最佳化演算法容易陷入區域極値,而加入”自我適應”的概念之後,參數可以選取到較佳的數值,可以大幅度改善動態差異形演化法的搜尋能力與提升演算法的強健性。
    第二個貢獻在研究埋藏於自由空間、半空間與三層空間二維散射體的電磁影像重建。此研究分別以有限時域差分法 (FDTD) 與動差法(MoM)為基礎,利用最佳化方法於時域重建埋藏於不同空間中二維散射體之特性參數。。
    This dissertation presents a new stochastic optimization algorithm for high dimensional test functions and two-dimensional inverse scattering problem. There are two contributions of this dissertation, the first point of the stochastic optimization algorithms are tested in nine different benchmark functions and found that the idea of approaching the “Best” during the course of optimization procedure are easy to fail into local optimal solution. However, the algorithm of SADDE is a self-adaptive version of DDE, which is processed of self-adaptibility and the ability of approaching the “Best”. Based on the self-adaptive concept, it can improve the robustness of the algorithm.
    The second point is presented the studies of some stochastic optimization methods for the shape reconstruction and permittivity distribution of two-dimensional scatterers. The scatterers are located in free space, or embedded in a three-layered material medium, respectively. In time domain, Finite-difference time-domain (FDTD) technique is employed for electromagnetic analyses for both the forward and inverse scattering problems, while the reconstruction problem is transformed into optimization one during the course of inverse scattering.
    The idea is to perform the image reconstruction by utilization of some optimization scheme to minimize the discrepancy between the measured and calculated scattered field data. Four optimization schemes are tested and employed to search the parameter space to determine the shape, location and permittivity of the two-dimensional scatterers. They are asynchronous particle swarm optimization (APSO), particle swarm optimization (PSO), dynamic differential evolution (DDE) and self-adaptive dynamic differential evolution (SADDE).
    The suitability and efficiency of applying the above methods for microwave imaging of two-dimensional scatterers are examined in this dissertation. The statistical performances of these algorithms are compared. The results show that SADDE outperforms PSO, APSO and DDE in terms of the ability of exploring the optima. However, these results are considered to be indicative and do not generally apply to all optimization problems in electromagnetics.
    Appears in Collections:[電機工程學系暨研究所] 學位論文

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