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研究生:呂月春
研究生(外文):Yueh-Chun Lu
論文名稱:以粒子群最佳演算法設計通訊通道等化器
論文名稱(外文):Design of the Equalizers for Communication Channels Based on Particle Swarm Optimization
指導教授:蘇德仁蘇德仁引用關係
指導教授(外文):Te-Jen Su
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:電子工程系
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:2009
畢業學年度:97
語文別:中文
論文頁數:76
中文關鍵詞:粒子群最佳演算法等化器有限脈波響應無限脈波響應
外文關鍵詞:Particle swarm optimizationFinite Impulse ResponseInfinite Impulse Response
相關次數:
  • 被引用被引用:1
  • 點閱點閱:175
  • 評分評分:
  • 下載下載:2
  • 收藏至我的研究室書目清單書目收藏:0
本篇論文旨在使用粒子群最佳演算法(Particle swarm optimization,PSO)提出通訊通道等化器之設計。PSO用較少的參數設定及快速收斂,是一種以族群為基礎的最佳化搜尋技術。通訊系統其主要之工作是確保訊息從發送端到接受端,而透過通道能夠有效且正確的傳送訊息,所以需要有一個等化器來將接收之訊號還原成原本之訊號。
在本篇論文裡,我們運用粒子群最佳演算法求有限脈波響應(Finite Impulse Response, FIR)等化器和無限脈波響應(Infinite Impulse Response, IIR)等化器,並分析其特性以驗證我們所提出的方法有效性。
This paper aims to design a communication channel equalizer based on Particle Swarm Optimization (PSO). Due to the features of swarm searching, PSO can use the few parameter hypotheses and processes and the rapid convergence. Communication systems mainly guarantee that the information can be delivered from transmitter to the receiver. However, due to the unideal channel effect via multi-path problem, applying an equalizer to recover the received signal should be considered.
In this paper, we utilize PSO algorithm to construct the limited pulse wave response (Finite Impulse Response, FIR) equalizer and infinite pulse wave response (Infinite Impulse Response, IIR) one. Then, the analysis of the characteristics of the proposed equalizer verifies the effectiveness of the proposed method.
中文摘要----------------------------------------i
英文摘要----------------------------------------ii
致謝-------------------------------------------iii
目錄--------------------------------------------iv
圖目錄------------------------------------------vii
表目錄------------------------------------------x
第一章 緒論--------------------------------------1
1.1研究動機----------------------------------1
1.2研究目的----------------------------------4
1.3論文架構----------------------------------5
第二章 基因演算法---------------------------------6
2.1 簡介------------------------------------6
2.2 基因演算法操作流程------------------------7
2.3 變數編碼與解碼----------------------------9
2.4初始族群----------------------------------10
2.5 適應函數---------------------------------11
2.6基因運算----------------------------------11
2.7終止條件----------------------------------17
第三章 粒子族群最佳化演算法-----------------------18
3.1最佳化問題 ---------------------------------19
3.2群體智慧-----------------------------------21
3.3粒子群最佳化之發展背景-----------------------23
3.4粒子群最佳化演算法介紹-----------------------24
第四章 系統模型描述與研究方法------------------------30
4.1 系統模型描述-------------------------------30
4.2 研究方法----------------------------------33
4.2.1 FIR濾波器-------------------------------33
4.2.2 IIR濾波器-------------------------------35
4.2.3最小均方誤差------------------------------37
4.3 應用PSO演算法訓練FIR等化器------------------39
第五章 模擬結果------------------------------------41
5.1 實例一 -----------------------------------42
5.2 實例二------------------------------------50
第六章 結論 ---------------------------------------58
參考文獻 ------------------------------------------59
發表論文-------------------------------------------63
自述-----------------------------------------------64
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