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研究生:楊紘權
研究生(外文):Hung-Chung Yang
論文名稱:應用基因演算法於通訊系統之研究
論文名稱(外文):Using Genetic Algorithms on Communication System
指導教授:歐謙敏歐謙敏引用關係
指導教授(外文):Chien-Min Ou
學位類別:碩士
校院名稱:清雲科技大學
系所名稱:電子工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:93
語文別:中文
論文頁數:49
中文關鍵詞:向量量化器基因演算法錯誤修正碼
外文關鍵詞:Vector QuantizationGenetic AlgorithmError Correct Coding
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本論文提出一種新型的基因演算法,能最佳化來源編碼與通道編碼。此演算法在來源編碼用一個通道最佳化向量量化器(channel-optimized vector quantization, COVQ),與一個在通道編碼的碼率穿孔摺積碼(rate-puncture convolutional coding, RCPC)。基因演算法(genetic algorithm, GA)是使用於對來源與通道編碼的並行設計。基因演算法提升了COVQ對初始碼字的選擇的碼率失真效能之強健性。另外它降低了對實現不同程度的錯誤保護系統最佳匹配於COVQ的計算時間。實驗數值的結果顯示出,當此演算法擁有較低的計算複雜度時,可以獲得近似最佳化的效能。
This paper presents a novel genetic algorithm for jointly optimizing source and channel codes. The algorithm uses a channel-optimized vector quantization (COVQ) for the source code, and a rate-punctured convolutional code (RCPC) for the channel code. The genetic algorithm (GA) is used for concurrent design of both source and channel codes. The GA enhances the robustness of the rate-distortion performance of the COVQ to selection of initial codebooks. In addition, it reduces the computational time for realizing the unequal error protection scheme best matched to the COVQ. Numerical results show that the algorithm attains near optimal performance while having low computational complexity.
中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 文獻回顧 1
1.2 研究動機與目的 4
1.3 研究方法與步驟 5
1.4 論文架構 5
第二章 基本理論介紹 6
2.1向量量化器 6
2.1.1向量量化器原理與架構 6
2.2通道最佳化來源編碼 8
2.3最佳化來原編碼 10
2.4基因演算法 10
2.4.1 初始族群 12
2.4.2 再生與選擇機制 13
2.4.3交配 15
2.4.4突變 17
第三章 使用基因演算法之並行設計 20
3.1 综何來源與通道編碼的設計 20
3.1.1 G-COVQ Algorithm 22
3.1.2 G-UEP Algorithm 24
3.1.3 GA-based Iterative Algorithm 25
3.1.4 GA-based Concurrent Algorithm 27
第四章 研究結果 30
第五章 結論 36
參考文獻 37
簡歷 39
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