臺灣博碩士論文加值系統

免手持通訊系統可以應用在免手持聽筒電話、視訊會議、遠距教學及遠端醫療等系統。而此種通訊系統必需解決聲學迴音之問題。可適性濾波器提供這個問題的有效解決方法，這些方法可概分為LMS家族及RLS家族演算法，而使用這些演算法的架構又可分為FIR和IIR架構。本論文針對這兩種架構來進行比較分析，發現使用IIR架構相對於FIR架構僅需較少的係數就可達到迴音消除，且對於噪音有抑制的效果，實驗的結果也驗證了我們的分析。
在真實通訊中，噪音也是我們要面對的一大問題，本論文也討論如何設計一噪音降低機制，並配合聲學迴音消除，完成一舒適的通訊系統。

Hands-free communications system finds several applications such as speaker-phone, tele-video conferencing systems, distance learning and medicine systems. A major problem in hands-free system is that of acoustic echo. Adaptive filtering has been considered as a promising way in solving this problem. These algorithms including LMS family and RLS family employed by FIR and IIR systems. This thesis studies the performance of equation-error adaptive IIR echo canceller. Analysis shows that the equation-error IIR canceller outperforms its FIR counterpart with much smaller number of coefficients. Extensive simulation and experiments validate our analysis.
The noise is also the problem we should overcome in the hands-free communications. Our analysis as well as experiments show the IIR echo canceller is capable of reducing the colored noise. We also present a scheme that deals with acoustic echo and noise.

中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 xiii
第一章 簡介 1
1.1背景介紹 1
1.2 論文組織 3
第二章 聯合聲學迴音消除器與噪音降低機制演算法及架構 4
2.1 聲學迴音消除器 4
2.2 噪音消除演算法 5
2.3 聯合聲學迴音消除器和降低噪音機制 8
2.3.1 AEC+NR 8
2.3.2 NR+AEC 9
2.3.3 NR+AEC+NR 9
第三章 適應性演算法之介紹 11
3.1 最小平均平方誤差(LMS)演算法 12
3.2 RLS演算法 14
3.3 FIR和IIR濾波器 15
3.3.1 FIR濾波器 15
3.3.2 IIR 濾波器 16
3.4 IIR適應濾波器演算法 16
3.4.1 IIR適應濾波器:輸出誤差方法 17
3.4.2 IIR適應濾波器:方程式誤差方法 20
3.5 FIR和IIR系統分析 23
3.5.1實驗一:迴音消除器在FIR和IIR架構下的比較 26
3.5.2實驗二:FIR和IIR架構的脈衝響應分析 35
3.5.3實驗三:加入近端語音 44
第四章 實驗模擬與結果 49
4.1 簡介 49
4.2 系統架構 49
4.3 實驗一：迴音消除器在FIR和IIR架構下的比較 51
4.4 實驗二：加入近端語音 57
4.5 實驗三 : 加入噪音降低機制 62
4.5.1當SNR=14.624 64
4.5.2當SNR=4.624 67
4.5.3當SNR=-5.376 70
4.6 實驗四:降低殘餘迴音 73
4.6.1 當SNR=14.624 74
4.6.1 當SNR=4.624 77
4.6.2 當SNR=-5.376 80
4.7 結論 83
第五章 結論 85
5.1 論文總結 85
5.2 未來工作 85
參考文獻

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