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研究生:廖輝雄
研究生(外文):Hui-Hsiung Liao
論文名稱:應用可變式步階值雙適應性演算法於噪音消除
論文名稱(外文):Applied Variable Step Size Algorithm to Dual-Adaptive Noise Canceller
指導教授:王延年
指導教授(外文):Yen-Nien Wang
學位類別:碩士
校院名稱:龍華科技大學
系所名稱:電子系碩士班
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:2006
畢業學年度:94
語文別:中文
論文頁數:64
中文關鍵詞:適應性噪音消除適應性濾波器LMS演算法
外文關鍵詞:Adaptive noise cancellerAdaptive filterLMS algorithm
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適應性濾波器一直是數位訊號處理一項重要的工具之ㄧ。基本上,它會隨著系統環境的狀況而改變,也就是說,適應性濾波器會依照欲估測之系統及其訊號參數,來做適應及調整。也由於它的這項優點,還有在設計上也較為簡單,所以近年來,適應性最小均方演算法(LMS)不僅引起廣大的注意,而且也被廣泛的使用。但其最大之缺點為其收斂速度慢,而且在選取步階值上,並沒有適當的方法,所以在實行上是較為困難的。因此,有許多學者致力於解決改善上述相關缺失。
本文提出一個可變式步階值函式演算法,來實現適應性噪音消除器(Adaptive Noise Canceller , ANC)。文中所使用適應性噪音消除器是利用兩個適應性濾波器所組成;主要濾波器(Main Filter , MF)和次要濾波器(Subfilter , SF)。次要濾波器是用來估測輸入訊號雜訊比(Signal-to-Noise Ratio , SNR),選定步階值係數給主要濾波器演算法做運算,經過不斷的調適使得最後輸出能夠降低噪音。經由MATLAB的實驗模擬,與Ikeda所提出的線性步階值函式和Ramadan提出的非線性步階值函式演算法相互比較,證明經由可變式步階值函式演算法能有效的達到預期的結果。
The adaptive filter is an important tool in digital signal processing. Depending on the changing of system conditions, an adaptive filter can be designed to estimate the parameters of the system and to adjust accordingly. Because of this advantage and its simplicity, the time-domain adaptive LMS algorithm has attracted a lot of attention and become one of the most widely used techniques in the past decade. However, because its converging speed is slow and there is no generally applicable rule in deciding the step size in each iteration, this technique is not very easy to implement. For this reason, many researchers have devoted their efforts in solving these problems.

This paper derives an algorithm to estimate the step size of the adaptive filter and simulate the behavior of the adaptive noise canceller in real time. The proposed ANC has two adaptive filters: a main filter (MF) and a subfilter (SF). The signal-to-noise ratio (SNR) of input signals is estimated using the SF. To reduce signal distortion in the output signal of the ANC, a step size for coefficient update in the MF is controlled according to the stimated SNR. Moreover, comparative studies on numerical experiments demonstrate the effectiveness of the proposed algorithm.
中文摘要 i
英文摘要 ii
誌 謝 iii
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 前言 1
1.2 研究動機和目的 3
1.3 論文架構 3
第二章 適應性演算法 5
2.1 Wiener Filter 5
2.2 最大梯度法(Steepest Descent) 13
2.3 LMS演算法原理 15
2.4 NLMS演算法原理 20
第三章 雙適應性噪音消除器 22
3.1 主動式噪音消除器架構 22
3.2 雙適應性噪音消除器架構 28
3.2.1 主要濾波器(Main Filter) 29
3.2.2 次要濾波器(Sub Filter) 31
3.3 線性步階值函式 33
3.4 非線性步階值函式 34
3.5 結論 36
第四章 可變式步階值演算法 37
4.1 步階值 39
4.2 模擬結果 41
第五章 結論與未來展望 61
5.1 結論 61
5.2 未來展望 62
參考文獻 63
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[2] Widrow, J. R, J. M. Glover and McCool et al., “Adaptive Noise Cancelling Principles and Applications,” Proceedings IEEE, vol. 63, pp. 1692-1716, Dec., 1975.

[3] Ikeda, S. and A. Sugiyama, “An Adaptive Noise Canceller with Low Signal Distortion for Speech Codecs,” IEEE Trans. Signal Processing, vol 47, no. 3, pp. 665- 674, March, 1999.

[4] Ramadan, Z. and A. Poularikas, “A Variable Step-Size Adaptive Noise Canceller Using Signal to Noise Ratio as the Controlling Factor, ” Proc. of the 36th IEEE Southeastern Symposium on System Theory (SSST), Atlanta, Georgia, March, 2004.

[5] Boll, S. F. and D. C. Pulsipher, “Suppression of Acoustic Noise in Speech Using Two Microphone Adaptive Noise Cancellation,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 28, no. 6, pp. 752-753, Dec., 1980.

[6] B. Widrow and S.D. Stearns, Adaptive Signal Processing, Prentice Hall, 1985.

[7] Harrison, W. A., J. S. Lim and E. Singer, “A New Application of Adaptive Noise Cancellation,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 34, no. 1, pp. 21-27, Jan., 1986.

[8] Al-Kindi, M. J. and J. Dunlop, “A Low Distortion Adaptive Noise Cancellation Structure for Real Time Applications,” in Proc. IEEE ICASSP, vol 12, pp. 2153-2156, Apr., 1987.

[9] Greenberg, J. E., “ Modified LMS Algorithms for Speech Processing with An Adaptive Noise Canceller,” IEEE Trans. On Speech Arid Audio Processing, vol. 6, no. 4, pp. 338-351, July, 1998.

[10] Paliwal, K. K. and A. Basu, “A Speech Enhancement Method Based on Kalman Filtering,” Proc. IEEE ICASSP, vol. 12, pp 177-180, Apr., 1987.

[11] Haykin, Simon S., Adaptive Filter Theory, Prentice Hall, 2002.

[12] Clarkson, Peter M., Optimal and Adaptive Signal Processing, CRC Press, 1993.

[13] Hyun-Chool Shin, Sayed, A.H. and Woo-Jin Song, “Variable Step-Size NLMS and Affine Projection Algorithms,” IEEE Signal Processing Letters, vol. 11, no. 2, Feb., 2004.

[14] Shaoli Kang, Yang Xiao and Zhengding Qiu, “A Novel Adaptive Noise Canceller with Master-Slave Structure,” Electronics, Circuits and Systems, 2000. ICECS 2000. The 7th IEEE International Conference on, vol. 1, pp 487-490, Dec., 2000.

[15] Mikhael, W. F. Wu, L. Kazovsky, G. Kang, and L. Fransen, “Adaptive filters with individual adaptation of parameters,” Circuits and Systems, IEEE Transactions on, vol. 33, no. 7, July, 1986.

[16] Gardner, W., B. Agee, “Two-Stage Adaptive Noise Cancellation for Intermittent-Signal Applications (Corresp.) ,” Information Theory IEEE Transactions on, vol. 26, no. 6, Nov., 1980.
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