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歡迎踴躍選修英文短期課程-106/10/24(二)-10/28(六) Dr. Jan Geldmacher, SWG SportWerk GmbH & Co. KG, Dortmund, Germany, 1學分
 

各位同學,

本系擬於10/24()-10/28()安排短期密集課程:ET5926701電子工程專論()1學分。上課相關資料如下。有意選修者,請於10/17()填妥附之選課單請指導教授簽名後繳至EE-404或掃瞄回傳。謝謝!

Dear students,

Our department intends to open an intensive short-term course. The course description is as follows:

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[Course Code & Name]  ET5926701電子工程專論()  (Special Topics on Electronic Engineering (6))

[Title]  Advanced digital signal processing: High-resolution frequency estimation approaches with applications

[Instructor]  Dr. Jan Geldmacher, Co-founder, R&D engineer, SWG SportWerk GmbH & Co. KG, Dortmund, Germany

[Class dates]

24th Oct.(Tues.) -27th Oct.(Fri.)     18:25-21:05 (A,B,C) (Every day)

28th Oct. (Sat.)                                     09:10-12:10 &13:20-16:40 (2,3,4&6,7,8) (One day)

[Duration] 18 hours , including tutorials and MATLAB projects

[Credit] 1     [Course language] English     [Class Room] IB-712

 

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Description

The problem of estimating and tracking the fundamental frequency of a sensor signal is often found in practical applications. These applications can be as different as the monitoring of the health status of the wide area power grid or the detection of human vital signals from ECG data or motion sensors. Often the requirement is to have a high-resolution frequency estimate with feasible, realtime implementation complexity. This lecture introduces digital signal processing algorithms to estimate the fundamental frequency of a digital signal processing system. We focus on methods that can be represented using simple linear algebra techniques and which can be applied to practical signal processing problems. Realworld medical sensor data will be used during the course to illustrate the principles. The course consists of 6 parts. Each part consists of a lecture, an assignment/tutorial and a MATLAB project. Then students will work in groups on the assignments and MATLAB projects to apply theory to practical problems.

Credit points

Students are required to present their project solutions during the class.

Target audience

Students interested in modern digital signal processing algorithms and MATLAB.

Required skills

The lecture is designed to be self-contained. MATLAB knowledge and basic mathematical skills, ie. matrix/vector computations, will be helpful.

Outline

Course 1: Introduction

• Introduction to digital signal processing (DSP)

• Applications, medical signal examples and problems (BCG sensor, ECG, Airflow PSG)

• Basics of DSP and systems

• Quantization, convolution, autocorrelation

• Assignment / Tutorial

• Project: Detect heart rate from ECG signal using autocorrelation

Course 2: Signal Transformations, Non-parametric Frequency estimation 1 / 2

• Basics of linear transformations

• Discrete cosine Transform (DCT)

• Discrete Fourier Transform (DFT)

• Assignment / Tutorial

• Project: Image compression based on DCT

Course 3: Signal Transformations, Non-parametric Frequency estimation 2 / 2

• Fast Fourier transform (FFT)

• Spectrogram

• Assignment / Tutorial

• Project: Detection of respiration rate from airflow signal using a spectrogram

Course 4: Detection based on linear filter

• Linear systems of equations

• Estimation and detection using filter

• Assignment / Tutorial

• Project: Detection of heart rate from ECG signal using an LS filter

Course 5: Subspace algorithms, Parametric frequency estimation 1 / 2

• Introduction to matrix subspaces

• Matrix decompositions

• Eigenvalue and singular value decompositions

• MUSIC algorithm

• Concept of signal and noise subspaces

• Assignment / Tutorial

• Project: Detection of respiration rate from chest movement signal using MUSIC algorithm

Course 6: Subspace algorithms, Parametric frequency estimation 2 / 2

• ESPRIT algorithm

• Assignment / Tutorial

• Project: Detection of respiration rate from chest movement signal using ESPRIT algorithm

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         電子系短期密集課程人工選課

 

              (English Short Course Application Form)

 

選課日期:即日起1061017  (Deadline: 17th Oct. 2017)

系所、班別

Department

   

Student ID

  

Name

聯絡電話

Telephone No.

指導教授簽名

(Advisor's signature)

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課程資料:

 

課程名稱

Course Name and Title

學分

Credit

授課教授

Instructor

上課時間

Class dates & Class hours:

教室

Room

ET5926701電子工程專論()

[Title] Advanced digital signal processing: High-resolution frequency estimation approaches with applications

1

Dr. Jan Geldmacher

24th Oct.(Tues.) -27th Oct.(Fri.)

18:25-21:05

(A,B,C) (Every day)

IB-712

28th Oct. (Sat.)

09:10-12:10 &13:20-16:40

(2,3,4&6,7,8) (One day)

 

選課期間自即日起至10/17(),請填妥簽名後繳至EE-404或掃瞄回傳 huang1208@mail.ntust.edu.tw 黃雪芬小姐收。

The application deadline is 17th August 2017, Please submit to EE-404 or mail to huang1208@mail.ntust.edu.tw Ms. Huang.

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