臺灣博碩士論文加值系統

主動式聲音特性化(active sound profiling)，是一種針對主訊號進行頻譜塑型的方式。藉由調整給予系統的指令訊號(command signal)，可對主音源訊號做消音、減音、不變或是放大等處理。在進行主動式聲音特性化時，系統常受到不相關音源的影響而降低性能表現，本論文將探討在主動式聲音特性化的過程中，如何提升演算法的收斂性能並解決此不相關音源對系統的影響。主動式聲音特性化演算法internal model FxLMS，因為結構與傳統的FxLMS的相似性，而有收斂緩慢的問題，藉由正規化演算法，並加入置換誤差(commutation error)的考量，可讓演算法在同樣的階數下採用更大的步階值，提升系統的收斂速度。為了解決系統受到不相關音源影響而導致性能降低的問題，本文先將常數步階值，修改為指數遞減型步階，讓系統的步階初始值能提升，並隨著時間逐步下降，此種方式不但能加快收斂速度，減輕不相關音源對系統性能的影響，還可以讓系統保有良好的穩態響應，但是，無法消除不相關音源。因此，本文於原有的前饋式的控制器中，加入一個干擾補償器，接著再串連一個回饋式控制器；其中，將會以干擾補償器來得出估測的不相關音源訊號；並讓前饋式控制器中的誤差訊號扣除此估測的訊號後，再送回前饋式控制器中做更新；同時，回饋式控制器將以此估測的不相關音源訊號作為參考訊號，並進行消除。藉由此種模式讓系統能在對主音源進行主動聲音特性化的同時又能減小甚至消除不相關音源，讓演算法的應用更為彈性。於本文的多頻模擬中，可以得知此種新型演算法的效能，輸入的主訊號可很好的作縮小或放大，而在此同時不相關音源可以有效的被消除。而於實驗中，也展現出了模擬時一樣的效果，驗證了本篇所提出之新型主動式聲音特性化演算法之性能。

Active sound profiling (ASP) is a strategy to shape the spectrum of the primary signal. According to a given command signal, a system can be made to either cancel or enhance a primary sound. In practical ASP applications, an interference (uncorrelated sound) can easily affect the system and degrade the system performance. In this thesis, a novel hybrid ASP algorithm and several schemes are proposed to deal with the problem caused by the interference. Due to the structure problem, the conventional ASP algorithm, internal model FxLMS, has a problem of slow convergence. In order to fix this problem, two schemes have been used in this thesis. One is to normalize the step size. The other is to incorporate a commutation error into the algorithm. By implementing these schemes, convergence speed of the algorithm can be made faster than that of before. To deal with the interference influence, an exponential decay step size is adopted to replace the constant normalized step size, so that the convergence speed can be fast and the performance degradation caused by interference can reduce. In order to further cancel the interference, we use a structure of three filters including a feedforward filter, a supporting filter and a feedback filter. The supporting filter can be used to obtain an estimate of the disturbance. This allows the feedforward filter to deal with the reference signal and the feedback filter to deal with the disturbance, separately. The proposed algorithm can possess both abilities of active sound-profiling and interference rejection at the same time, demonstrating in the results of simulations and experiments.

致謝 i
摘要 ii
ABSTRACT iii
目錄 iv
圖目錄 vi
表目錄 x
第一章 緒論 1
1.1. 研究動機 1
1.2. 文獻回顧 1
1.3. 論文概要 4
第二章 主動式聲音特性化 5
2.1. 傳統的演算法 7
2.2. 既有演算法之改善 9
第三章 具有不相關音源之主動式聲音特性化 11
3.1. 具有不相關音源之主動式聲音特性化系統描述 11
3.2. 指數遞減型步階 13
3.3. 含干擾補償器之混合型主動式聲音特性化演算法 14
第四章 電腦模擬 18
4.1. Internal Model NFxLMS/CE演算法 22
4.2. EDSS-Internal Model NFxLMS/CE演算法 27
4.3. EDSS-HASP/CE_DC演算法 33
第五章 實驗 40
5.1. 實驗架構 40
5.2. Internal Model NFxLMS/CE演算法 43
5.3. EDSS-Internal Model NFxLMS/CE演算法 48
5.4. EDSS-HASP/CE_DC演算法 53
第六章 結論與未來展望 62
6.1. 結論 62
6.2. 未來展望 62
參考文獻 64

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