時頻分析與小波轉換

   Time-Frequency Analysis and Wavelet Transform

                            授課者:丁建均

 

上課地點:電機二館 143 室

上課時間:星期四上午 9 : 10 ~ 12 : 10

上課資料:講義  (請大家在每週上課前,來這個網頁把上課講義列印好)

Office 明達館723,    TEL 33669652  

實驗室網頁:http://disp.ee.ntu.edu.tw/       

Office hour 每一天下午都可以來找我

E-mail:  jjding@ntu.edu.tw   

助教:待安排

 

 

一、上課講義下載專區           

09月22日上課資料  

 

 

 

 

二、Tutorials 專區

(Part 1: Time Frequency Analysis)

S Transform   

Recent Development of the S Transform (2014)     

Recent Development of the S Transform (2016)                                                                             

Gabor Feature and its Applications                                  

Cohen's Class Distribution                                                      

Matching Pursuit  

Matching Pursuit for Compressed Sensing        

Multiscale Entropy                          

Generalized Spectrogram   

Prolate Spheroidal Wave Functions      

A Novel Time-Frequency Analysis Method    

 

(Part 2: Applications of Time Frequency Analysis)

Time-Frequency Analysis for Music Signal Analysis              

Time-Frequency Analysis for Doppler Ultrasound Signals

Time-Frequency Analysis for Seismology (1)                         

Time-Frequency Analysis for Seismology (2)

Time-Frequency Analysis for for EMG signals                       

Time-Frequency Analysis for Biomedical Engineering

Time Frequency Analysis for Acoustics (1)                            

Time Frequency Analysis for Acoustics (2)       

Time Frequency Analysis for Chinese Tone Identification                       

Time-frequency Analysis for Vocal Signal Compression                   

Time Frequency Analysis for Voiceprint Recognition            

Time-Frequency Analysis for ECG signals   

Time-Frequency Analysis for Filter Design                       

Time Frequency Analysis for Sampling   

Time Frequency Analysis for Accelerometer Signals   

Time Frequency Analysis for Radar Image Processing   

 

(Part 4: Wavelet Transforms)

Morlet Wavelet                                              

Haar Transform and Its Applications        

Directional Wavelet Transform_Curvelet                                

Directional Wavelet Transform_Shearlet

Directional Wavelet Transform_Contourlet

Complex Wavelet Transform                                                  

Bionic Wavelet Transform               

Lifting Scheme for Wavelet Transforms                                 

Recent Development of Wavelet Transforms      

 

(Part 5: Applications of Wavelets for Image Processing)

Wavelet for Edge Detection                                                    

Wavelet for Filter Design           

Discrete Wavelet Transform for JPEG2000                            

Tier 1 and Tier 2 for JPEG2000                

JPEG2000 以外的小波轉換影像壓縮技術                                                                   

Wavelet for Image Fusion

Wavelet for Pattern Recognition           

Wavelet for Fingerprint Matching           

Wavelet for Image Denoising (1)                                             

Wavelet for Image Denoising (2)      

Wavelet for Video Compression       

Haar Transforms for Feature Extraction                   

 

(Part 5: Other Applications of the Wavelet Transform)

小波轉換於心電圖分析及腦機介面上的應用                   

小波轉換於腦電訊號上的應用         

小波轉換、EMD等方法於生理訊號前處理之效能分析      

Damage Detection via Wavelet Transform                               

Wavelet Analysis of Financial Variables                               

Wavelet for Music Signal Analysis (1)                                    

Wavelet for Music Signal Analysis (2)

Wavelet for Biomedical Signal Processing                              

Wavelet Analysis for Accelerometer Signals    

Wavelet for Acoustics                             

Fetal ECG Extraction and Fiducial Points Detection by Haar Wavelet Transforms                                                                                              

 

(Part 6: Hilbert Huang Transform)

Hilbert Huang Transform for Climate Analysis                       

Hilbert Huang Transform for Acoustics    

Recent Development of the Hilbert-Huang Transform            

Economic Data Analysis by Hilbert Huang Transforms 

Hilbert-Huang Transform for Geology                                    

Hilbert-Huang Transform for Spectral Doppler  

Hilbert-Huang Transform for Image Processing                      

Hilbert-Huang Transform for Biomedical Signal Processing        

Two-Dimensional Hilbert-Huang Transform     

B Spline  

 

(Part 7: Fractional Fourier Transform)

Fractional Fourier Transform                                                    

Linear Canonical Transform

Fractional Fourier Transform for Filter Design (1)                    

Fractional Fourier Transform for Filter Design (2)  

Linear Canonical Transform for Optical System Analysis         

Recent Development of the Fractional Fourier Transform  

Fractional Fourier Transform for Random Process Signal Analysis   

 

 

三、評分方式

平時分數: 15 scores 

基本分11.8分,各位同學皆可拿到(非缺席狀況嚴重)

外再根據上課回答問題加分 

 

Homework: 60 scores

(5 times, 3 週一次)

(請自己寫,和同學內容相同,將扣 60% 的分數,就算寫錯但好好寫也會給 40~95% 的分數,
 遲交分數打
8 折,不交不給分。不知道如何寫,可用 E-mail 和我聯絡,或於上課時發問)

 

Term paper 25 scores

方式有四種

(1) 書面報告 (10頁以上(不含封面),中英文皆可,11或12的字體,題目可選擇和課程有關的任何一個主題,格式和一般寫期刊論文或碩博士論文相同,包括 abstract, conclusion, 及 references,並且要分 sections,必要時有subsections。 )

(2) Tutorial (和書面報告格式相同,但18頁以上,題目由老師指定,以清楚的介紹一個主題的基本概念和應用為要求,選擇這個項目的同學,學期成績加 3分) 

(3) 口頭報告 (限四個人,每個人 30~40分鐘,題目可選擇和課程有關的任何一個主題,選擇這個項目的同學,學期成績加 2分)

(4) 編輯 Wikipedia (中文或英文網頁皆可,至少 2 個條目,但不可同一條目翻成中文和英文。限和課程相關者,自由發揮,越有條理、有系統的越好)

 

 

四、推薦參考書籍:

· S. Qian and D. Chen,  Joint Time-Frequency Analysis: Methods and Applications, Prentice-Hall, 1996.

· S. Mallat, A Wavelet Tour of Signal Processing: The Sparse Way, Academic Press, 3rd  edition, 2009.

· L. Cohen, Time-Frequency Analysis, Prentice-Hall, New York, 1995.

· K. Grochenig, Foundations of Time-Frequency Analysis, Birkhauser, Boston, 2001.

· L. Debnath, Wavelet Transforms and Time-Frequency Signal Analysis, Birkhäuser, Boston, 2001.

 

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