BMM041 Applied Digital Signal Processing

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code BMM041
Name Applied Digital Signal Processing
Term 2022-2023 Academic Year
Term Spring
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Doç. Dr. AHMET AYDIN
Course Instructor
1


Course Goal / Objective

Students learns digital signal processing methods. Achieve the ability of performing those methods on a computer. Gain experience in biosignal processing.

Course Content

Biosignals, ADC Conversion, Convolution, Correlation Based Signal Analysis Methods, Fourier Series Analysis, Power Spectrum, Welch's Method, Z-Transform, FIR Filter, IIR Filter, Short Time Fourier Transform, Wavelet Analysis

Course Precondition

None

Resources

J.L. Semmlow, B. Griffel, "Biosignal and Medical Image Processing"

Notes

J.M. Giron-Sierra, "Digital Signal Processing with Matlab Examples I, II, III"


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Learns ADC Steps and Sensors
LO02 Learns biosignals and noise analysis
LO03 Learns correlation and covariance and applies them
LO04 Can design and apply a digital filter to the signal.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal To be able to solve scientific problems encountered in the field of medicine and medical technologies by applying current and advanced technical approaches of mathematics, science and engineering sciences. 5
PLO02 Yetkinlikler - Öğrenme Yetkinliği To have a knowledge of the literature related to a sub-discipline of biomedical engineering, to define and model current problems. 4
PLO03 Beceriler - Bilişsel, Uygulamalı Ability to analyze data, design and conduct experiments, and interpret results 5
PLO04 Beceriler - Bilişsel, Uygulamalı Developing researched contemporary techniques and computational tools for engineering applications 4
PLO05 Beceriler - Bilişsel, Uygulamalı To be able to analyze and design a process in line with a defined target 5
PLO06 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Conducting scientific studies with a medical doctor from an engineering perspective. 4
PLO07 Yetkinlikler - İletişim ve Sosyal Yetkinlik Expressing own findings orally and in writing, clearly and concisely.
PLO08 Yetkinlikler - Öğrenme Yetkinliği To be able to improve oneself by embracing the importance of lifelong learning and by following the developments in science-technology and contemporary issues.
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Ability to act independently, set priorities and creativity.
PLO10 Yetkinlikler - Alana Özgü Yetkinlik Being aware of national and international contemporary scientific and social problems in the field of Biomedical Engineering.
PLO11 Yetkinlikler - Alana Özgü Yetkinlik To be able to evaluate the contribution of engineering solutions to problems in medicine, medical technologies and health in a global and social context.


Week Plan

Week Topic Preparation Methods
1 Introduction Read the Lecture Syllabus Öğretim Yöntemleri:
Anlatım
2 Biosignals, Sensors and ADC Steps Read Chapter 1 of the lecture book Öğretim Yöntemleri:
Anlatım
3 Biosignal Measurement, Noise ana Analysis Read Section 2.1 and Section 2.2 of the lecture book Öğretim Yöntemleri:
Anlatım
4 Basis Functions, Correlation and Covariance Read Section 2.3 of the lecture book Öğretim Yöntemleri:
Anlatım
5 Convolution and Impulse Response Read Section 2.3 of the lecture book Öğretim Yöntemleri:
Anlatım
6 Discrete Fourier Transform and Windows Read Chapter 3 of the lecture book Öğretim Yöntemleri:
Anlatım
7 FIR Filters and Appliceations Read Section 4.1 - 4.4 of the lecture book Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Lecture Notes Ölçme Yöntemleri:
Yazılı Sınav
9 IIR Filters and Applications Read Section 4.5 of the lecture book Öğretim Yöntemleri:
Anlatım
10 Welch's Method, Modern Spectral Analysis: MA, AR, ARMA Read Chapter 5 of the lecture book Öğretim Yöntemleri:
Anlatım
11 Short Time Fourier Analysis Read Section 6.1 - 6.2 of the lecture book Öğretim Yöntemleri:
Anlatım
12 Wavelet Transform I: Basics Read Section 7.1 - 7.2 of the lecture book Öğretim Yöntemleri:
Anlatım
13 Wavelet Transform II: Applications Read Section 7.3 of the lecture book Öğretim Yöntemleri:
Anlatım
14 Term Project I Lecture Notes and Application Examples Öğretim Yöntemleri:
Anlatım
15 Term Project II Lecture Notes and Application Examples Öğretim Yöntemleri:
Anlatım
16 Term Exams Lecture Notes Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Lecture Notes Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 16.11.2022 01:43