臺灣博碩士論文加值系統

在通訊系統中，由於訊號在傳輸過程中會有雜訊干擾，因此在接收端便需要對收到的信號來做處理，以便使接收者能獲得原先所傳送的資料，為了有效降低通道傳送過程中，產生的符元干擾現象所造成的訊號失真，在接收端裝置等化器是必須的。
符元干擾是影響通訊系統效能的一個重要因素，為了使一開始所傳送的訊號可以被接收端正確的接收到，利用適應性通道等化器可以有效地消除由通道頻寬或多重路徑所造成的符元干擾。
在本篇論文裡，我們提出了改良型細菌搜尋最佳化演算法，包含了自適應和自適應細菌搜尋結合粒子群最佳化等方法，適應性通道等化器的權重值更新，是由前置資訊的更新進而完成最佳化的調整。最後，經由電腦模擬的結果來說明並分析其特性以驗證我們所提出的方法有效性。

In the communication systems, due to noise interference of signal transmission through channel, so the signal will need to be handled at the receiver, applying an equalizer recovering the received signal should be considered. Inter-symbol interference (ISI) is an important factor which affects the performance of communication systems, so that the originally transmitted symbols can be recovered correctly at the receiver, an equalizer can effectively eliminate ISI caused by band-limited channel or multipath.
In this thesis, we propose a self adaptive bacterial foraging oriented by particle swarm optimization (SABF-PSO) approach, to update the adaptive channel equalizer weights which are optimized. Finally, from the simulation results are given to verify the effectiveness of the proposed method.

中文摘要 ---------------------------------------------------------------------------------- I
英文摘要 ---------------------------------------------------------------------------------- II
誌 謝 ---------------------------------------------------------------------------------- III
目 錄 ---------------------------------------------------------------------------------- IV
圖 目 錄 ---------------------------------------------------------------------------------- VI
表 目 錄 ---------------------------------------------------------------------------------- VII
符號說明 ---------------------------------------------------------------------------------- VIII

一、緒 論---------------------------------------------------------------------------------- 1
1.1 研究背景-------------------------------------------------------------------------- 1
1.2 研究動機---------------------------------------------------------------------- 2
1.3 論文架構---------------------------------------------------------------------- 3

二、相關演算法之研究-------------------------------------------------------------------- 5
2.1 細菌搜尋最佳化演算法-------------------------------------------------------- 5
2.1.1 趨化-------------------------------------------------------------------------------- 5
2.1.2 群聚-------------------------------------------------------------------------------- 6
2.1.3 繁殖-------------------------------------------------------------------------------- 7
2.1.4 環境變遷-------------------------------------------------------------------------- 7
2.1.5 細菌搜尋最佳化演算法運算流程-------------------------------------------- 8
2.2 自適應細菌搜尋最佳化演算法-------------------------------------------- 9
2.2.1 自適應細菌搜尋最佳化演算法特性------------------------- --------------- 9
2.2.2 自適應性的趨化----------------------------------------------------------------- 10
2.2.3 自適應細菌搜尋最佳化演算法運算流程-------------------------------- 11
2.3 自適應細菌搜尋結合粒子群最佳化演算法-------------------------------- 12
2.3.1 粒子群最佳化演算法----------------------------------------------------------- 12
2.3.2 自適應細菌搜尋結合粒子群最佳化演算法特性-------------------------- 15
2.3.3 自適應細菌搜尋結合粒子群最佳化演算法運算流程-------------------- 16
2.4 最小均方演算法----------------------------------------------------------------- 19
三、系統分析與研究方法----------------------------------------------------------------- 21
3.1 系統描述-------------------------------------------------------------------------- 21
3.1.1 有限脈衝響應濾波器----------------------------------------------------------- 21
3.1.2 均方誤差法------------------------------------------------------- 24
3.3.1 位元錯誤率----------------------------------------------------------------------- 25
3.2 研究方法-------------------------------------------------------------------------- 26
3.2.1 以最小均方演算法應用適應性通道等化器-------------------------------- 26
3.2.2 以細菌搜尋最佳化演算法應用適應性通道等化器----------------------- 27
3.2.3 以自適應細菌搜尋最佳化演算法應用適應性通道等化器-------------- 31
3.2.4 以自適應細菌搜尋結合粒子群最佳化應用適應性通道等化器-------- 35

四、模擬結果-------------------------------------------------------------------------------- 39
4.1 簡介-------------------------------------------------------------------------------- 39
4.2 結果-------------------------------------------------------------------------------- 40
4.2.1 實例一----------------------------------------------------------------------------- 39
4.2.2 實例二----------------------------------------------------------------------------- 43

五、結論與未來展望------------------------------------------------------------- 46

參考文獻 ---------------------------------------------------------------------------------- 47
發表論文 ---------------------------------------------------------------------------------- 50
自 述 ---------------------------------------------------------------------------------- 51

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