臺灣博碩士論文加值系統

當我們處理具有相關性的訊號源時，使用傳統時域適應性限制性和非限制性最小均方值演算法，其收斂速度將會變得緩慢。因此，使得時間延遲估測的品質嚴重變差。為了改善這個問題，已有學者提出一種適應性限制性離散餘弦轉換最小均方值演算法解決。然而，任何正交轉換的使用將不對所有類型的訊號都能完全地把輸入訊號自相關矩陣對角化。事實上，在轉換域自相關矩陣中，重要的非對角元素將使得適應性限制性離散餘弦轉換最小均方值演算法的收斂品質變差。
為了進一步解決上述的問題，在本論文中，我們提出了適應性限制性修正式離散餘弦轉換最小均方值演算法來對所有類型的輸入訊號做時間延遲估測。除此之外，基於離散小波轉換的正交性，我們也提出了適應性限制性修正式離散小波轉換最小均方值演算法，並且把它應用在時間延遲估測的問題上。對於不同訊號源的類型而言，我們證明了這兩個提出的修正式限制性方法在時間延遲估測上，會得到較好的估測品質比使用非修正式的方法。此外，從模擬的結果，我們可以觀察出使用適應性限制性修正式離散餘弦轉換最小均方值演算法的估測品質稍微優於適應性限制性修正式離散小波轉換最小均方值演算法。

The convergence speed using the conventional approaches, viz., time-domain adaptive constrained and unconstrained LMS algorithms, becomes slowly, when dealing with the correlated source signals. In consequence, the performance of time delay estimation (TDE) will be degraded, dramatically. To improve this problem, the so-called transform-domain adaptive constrained filtering scheme, i.e., the adaptive constrained discrete-cosine-transform (DCT) LMS algorithm, has been proposed in [15]. However, the use of any one orthogonal transform will not result in a completely diagonal the input signal auto-correlation matrix for all types of input signals. In fact, the significant non-diagonal entries in the transform-domain auto-correlation matrix, will deteriorate the convergence performance of the algorithm.
To further overcome the problem described above, in this thesis, a modified approach, referred as the adaptive constrained modified DCT-LMS (CMDCT-LMS) algorithm, is devised for TDE under a wide class of input processes. In addition, based on the orthogonal discrete wavelet transform (DWT), an adaptive constrained modified DMT-LMS (CMDWT-LMS) algorithm is also devised and applied to the problem of TDE. We show that the proposed two modified constrained approaches for TDE does perform well than the unmodified approaches under different source signal models. Moreover, the adaptive CMDCT-LMS filtering algorithm does perform slightly better than the adaptive CMDWT-LMS filtering algorithm as observed from the simulation results.

Acknowlegementi
Abstractii
Contentsiii
List of Figures and Tablesv
Chapter 1 Introduction1
Chapter 2 Adaptive Constrained Modified DCT-LMS Filtering Algorithm
for Time Delay Estimation
2.1 Introduction3
2.2 Conventional Adaptive Constrained DCT-LMS Filtering Algorithm for TDE4
2.2.1 Statement of Signal Model for TDE4
2.2.2 Adaptive Constrained DCT-LMS Filtering Algorithm for TDE7
2.3 Adaptive Constrained Modified DCT-LMS Filtering Algorithm for TDE11
2.4 Computer Simulation Results13
Chapter 3 Adaptive Constrained Modified DWT-LMS Filtering Algorithm
for Time Delay Estimation
3.1 Introduction24
3.2 Discrete Wavelet Transform24
3.3 Adaptive Constrained Modified DWT-LMS Filtering Algorithm for TDE32
3.4 Computer Simulation Results36
Chapter 4 Conclusions44
Appendix A45
Appendix B48
Appendix C52
References54

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