BMM0049 Advanced Applications in Signal Processing

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

Information

Code BMM0049
Name Advanced Applications in Signal Processing
Term 2022-2023 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator


Course Goal / Objective

Transferring Adaptive Filters, Chaotic Systems, Non-Linear Systems, Knowledge Based Methods and Applications

Course Content

Autoregressive Model, Yule-Walker Equation Non-Parametric Analysis: Self-Analysis Frequency Estimation Optimal Signal Processing: Wiener Filters Adaptive Signal Processing Filter Banks Wavelet Analysis Principal Component Analysis (PCA) Independent Component Analysis (ICA) Chaotic and Non-Linear Systems Detection of Nonlinearity: Knowledge-Based Methods

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 Student can perform signal processing for nonlinear or chaotic systems
LO02 Can apply adaptive filters.
LO03 Can use modern Spectral Analysis methods.
LO04 Develops a digital system.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal To be able to reach new solutions by applying current and advanced technical approaches of mathematics, science and engineering sciences to current scientific problems encountered in the field of medicine and medical technologies. 5
PLO02 Yetkinlikler - Öğrenme Yetkinliği Having knowledge of the literature related to a sub-discipline of biomedical engineering, defining and modeling current problems, and being a specialist in that discipline. 5
PLO03 Beceriler - Bilişsel, Uygulamalı Analyzing data, making theoretical and simulation based designs, designing experiments and interpreting the results. 5
PLO04 Beceriler - Bilişsel, Uygulamalı Developing researched contemporary techniques, software, hardware and computational tools for engineering applications. 5
PLO05 Beceriler - Bilişsel, Uygulamalı To be able to analyze and design a process in line with a defined target.
PLO06 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği To be able to carry out scientific studies with medical doctors and members of other disciplines from an engineering point of view.
PLO07 Yetkinlikler - İletişim ve Sosyal Yetkinlik Expressing one's own findings orally and in writing, clearly and concisely, writing conference and journal papers.
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 The ability to act independently, set priorities and be creative.
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 Autoregressive Model, Yule-Walker Equation Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
2 Non-Parametric Analysis: Self-Analysis Frequency Estimation Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
3 Optimal Signal Processing: Wiener Filters Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
4 Adaptive Signal Processing I Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
5 Adaptive Signal Processing II Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
6 Filter Banks Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
7 Wavelet Analysis Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Reivew Ölçme Yöntemleri:
Yazılı Sınav
9 Principal Component Analysis (PCA) Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
10 Independent Component Analysis (ICA) Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
11 Chaotic and Nonlinear Systems I Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
12 Chaotic and Nonlinear Systems II Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
13 Detection of Nonlinearity: Knowledge-Based Methods Reading the relevant chapter in the book Öğretim Yöntemleri:
Anlatım
14 Application Examples I Review Öğretim Yöntemleri:
Anlatım
15 Application Examples II Review Öğretim Yöntemleri:
Anlatım
16 Term Exams Review Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review 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 06:48