臺灣博碩士論文加值系統

主動式噪音消除主要是應用適應性濾波器演算法來達成，其中以最小均方(Least Mean Square, LMS)及正規化最小均方(Normalized Least Mean Square, NLMS)等演算法的應用最為普遍。在NLMS的應用上，步階值和參考信號的功率大小對適應性濾波器而言，是非常重要的參數，會影響到整個NLMS的收斂速度及曡代的過程。在NLMS中步階值是由參考信號及收斂因子所決定，但一個固定的收斂因子值對時變的噪音並不能有好的抑制效果。為改善這個問題，本論文採用模糊理論結合NLMS 演算法並根據估測出的噪音信號及噪音信號之間的相對差值，決定收斂因子值。本論文使用德州儀器的數位信號處理器TMS320C6416發展板(DSK)，配合電容式麥克風擷取噪音信號，輸入至DSK中經由本論文採用的演算法估測噪音信號，產生反相噪音信號以達到噪音抑制的效果。最後以單頻噪音、雙頻噪音及隨機噪音來驗證系統的效能。

Adaptive filter algorithms are generally used for the achievement of active noise cancellation. Especially least mean square (LMS) and normalized least mean square (NLMS) are two of the most widely used algorithms. The step size and the power of reference signal in NLMS algorithm are the most critical parameters in adaptive filtering. They govern the convergence speed and the fluctuation of the NLMS adaptation process. Here the step size is decided not only by reference signal but also by convergence factor. Besides, a fixed convergence factor can not respond to time-varying channel parameters, thus leading to poor performance. In this work, a Fuzzy VSS-NLMS (Variable step size NLMS) method is used to determine the step size. The step size is determined not only by the estimate of noise signal but also the difference of noises. We also implement the algorithm in a practical system. The system is implemented using the TMS320C6416 DSK and thoroughly verified by a number of noise signals including single tone signal, dual tones signal and random signal. They all get good noise cancellation performance.

摘 要 I
ABSTRACT II
目錄 I
表目錄 III
圖目錄 IV
第 一 章 緒論 1
1-1 研究動機 1
1­2 研究目的 1
1-3 文獻回顧 2
1-4 本文架構 3
第 二 章 理論 5
2-1 噪音消除基本原理 5
2-2 第二路徑效應 6
2-3 第二路徑效應建模 7
2-4 LEAST MEAN SQUARE(LMS)演算法 8
2-5 NORMALIZED LEAST MEAN SQUARE(NLMS)演算法 11
2-6 模糊理論 12
2-6-1 模糊集合 12
2-6-2 模糊集合運算 14
2-6-3 模糊關係運算 14
2-6-4 模糊控制器 15
第 三 章 系統架構與設計 16
3-1 系統方塊圖 16
3-2 聲音感測電路 16
3-3演算法及數位信號處理程式發展 19
3-3-1 模糊可變步階值適應性濾波器 19
3-3-2 數位信號處理器程式發展 28
第 四 章 實驗結果與討論 35
4-1 模糊可變步階適應性濾波器模擬結果 35
4-1-1 以單頻信號當模擬噪音源 35
4-1-2 以複頻信號當模擬噪音源 38
4-1-3 以隨機信號當模擬噪音源 41
4-2 模糊可變步階適應性濾波器實際測試結果 44
4-2-1 以單頻信號當噪音源 44
4-2-2 以複頻信號當噪音源 46
4-2-3 以隨機信號當噪音源 49
4-3 實驗結果討論 51
第 五 章 結論與未來展望 52
5-1 結論 52
5-2 未來展望 52
參考文獻 54

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