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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 貝蘇章(Soo-Chang Pei) | |
| dc.contributor.author | Chi-Chung Lin | en |
| dc.contributor.author | 林志忠 | zh_TW |
| dc.date.accessioned | 2021-06-13T15:38:51Z | - |
| dc.date.available | 2008-07-10 | |
| dc.date.copyright | 2008-07-10 | |
| dc.date.issued | 2008 | |
| dc.date.submitted | 2008-07-09 | |
| dc.identifier.citation | [1] ID. Gabor, “Theory of communication,” J, IEE, part 111, pp. 429-411, Nw. 1946.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/37690 | - |
| dc.description.abstract | 本篇論文由四個主要的章節組成，在第二章節中，我們將介紹時頻分析的基本概念，一些比較常見的時頻分析以及它們的特性也會逐一的討論，例如：短時間傅利葉轉換和韋格納分布等等。除此之外，他們的優缺點以及一些取捨的問題也會在此處比較。
在第三章節中，我們將討論S轉換，R. G. Stockwell et al. [6] 於1996年提出S轉換並認為此轉換是由短時間傅利葉轉換和小波轉換推導而來的，和S轉換相關的理論也會在此處做些說明，例如：TT-transform、時時濾波、時頻濾波。我們提出一個新的可變視窗，和原本S轉換不同的是此視窗可以依據訊號的性質來調整解析度，以取得更好的時頻分布圖。 在第四章節中，我們提出計算DOST的快速演算法，由於IFFT的幫忙，我們可以比原來的計算方式快上好幾倍。一個新的少量戎餘離散S轉換將會在此提出，也會和原本的S轉換以及DOST做比較。 在最後一章，我們將探討未知語音訊號分離的問題，我們針對已有的分群方法做修改，和原本方法不同之處在於在訊號分離之前我們使用了STFT時頻濾波以及不同的比重公式。和soft-LOST演算法相比較，我們的方法有更好的結果。 | zh_TW |
| dc.description.abstract | There are four important chapters in this thesis. In chapter 2 we introduce the basic idea of time-frequency representation (TFR); some conventional TFRs, such as Short Time Fourier transform (STFT), Wigner distribution and etc., and their properties will be discussed respectively. Besides, we will also compare their major advantages, disadvantages, and some trade-off.
The S-transform, a combination of STFT and Wavelet transform, proposed by R. G. Stockwell et al. in 1996 [6], will be illustrated in chapter 3. Some related topics, TT-transform, time-time filter, and time-frequency filter, will also be mentioned. We propose a novel window to adjust the time-frequency resolution of the original S-transform in order to get a better representation of the signal and do time-frequency filtering. We propose a fast algorithm for discrete orthonormal S-transform (DOST) in chapter 4, and due to the help of IFFT our new algorithm could run much faster than the original algorithm. A new modified discrete S-transform with less redundancies will be discussed here and compared with the original S-transform and DOST. In the final chapter, a modified clustering method for Blind Audio Source Separation will be proposed; our major contributions are the additional STFT time-frequency filtering before the source estimation and different weighting formula. Comparing the soft-LOST with our method, our method really does a better job. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T15:38:51Z (GMT). No. of bitstreams: 1 ntu-97-R95942039-1.pdf: 4007598 bytes, checksum: bbea102b6fb37acfb7441095dabe210f (MD5) Previous issue date: 2008 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 iii Abstract v Chapter 1 Introduction 1 Chapter 2 Time-frequency Representations 5 2.1 Introduction 5 2.2 Conventional Fourier Transform 6 2.3 Time-frequency Representations 9 2.4 Application and Conclusion 21 Chapter 3 Novel S-transform with the Special Varying Window 25 3.1 Introduction 25 3.2 S-transform 26 3.3 TT Transform 28 3.4 Time-frequency Filter and Time-time Filter 29 3.5 Novel S-transform with the Special Varying Window 30 3.6 Several Examples for Adjusting the Resolution 31 3.7 Filtering Out the Interference Noise Using Special Window 36 3.8 Conclusion 41 Chapter 4 Discrete S-transform 43 4.1 Introduction 43 4.2 Properties of S-transform 44 4.3 Discrete Orthonormal S-transform (DOST) 46 4.4 Fast Algorithm of the DOST 50 4.5 Discrete S-transform with Less Redundancies 54 4.6 Conclusion and Future Work 58 Chapter 5 Effective Clustering Method for Blind Audio Separation 59 5.1 Introduction 59 5.2 Sparsity and Mixture Matrix Types 60 5.3 Soft-LOST Method 63 5.4 Clustering Method 66 5.5 Experiments and Comparisons 71 5.6 Conclusion and Future Work 76 Chapter 6 Conclusion and Future Work 78 Reference 80 | |
| dc.language.iso | en | |
| dc.title | 可變視窗時頻域S轉換及群聚訊號分離法 | zh_TW |
| dc.title | S-transform with the Special Varying Window and Clustering Method for Blind Audio Separation | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 丁建均(Jian-Jiun Ding),王鵬華(Peng-Hua Wang),祁忠勇(Chong-Yung Chi) | |
| dc.subject.keyword | 時頻分佈,S轉換,時頻濾波,離散正規正交S轉換,未知語音訊號分離法, | zh_TW |
| dc.subject.keyword | time-frequency representation,S-transform,time-frequency filter,discrete orthonormal S-transform,blind audio source separation, | en |
| dc.relation.page | 83 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2008-07-09 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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