This course uses an applied, research problem-based approach to learning. That is, instead of the conventional lectures and exams, the course will consider a number of real research problems and learn the necessary tools in the context of solving each of these research problems. This approach has the following advantages:
The learning process will be as follows:
Topic-specific handouts will be given for each research problem.
All research problems will be investigated using a scientific programming language preferably Matlab or Octave (open source program similar to Matlab)
Answer each question with a brief answer describing the idea and steps
Feel free to give your own opinion about the exam problems based on your own experiences
Justify your answers with your own logic to explain them
You are allowed to discuss the problems with other students but not copy their answers
Send your answers as an electronic document by December 26, 2015
Lecture 3 Code: code1(ECG BW filters) code2(zero-phase filters)
Report on this problem is to be submitted in electronic form by e-mail
Material Handouts: HO1
Sample code for feature extraction + simple feature selection
Research problem description (use links inside to download data and sample code)
Academic Journal Paper Search sites (Recommended - Accessible from KAU):
Microsoft OneNote (Nice tool for lab notebook documentation of research)
Template for conference papers: EMBC 2015 Sample Paper
Matlab Primer (Official Mathworks Material)
Matlab Introduction (University of Dundee)
Grading Policy
Assignments |
60% |
Research Reports | 40% |
Please follow the links here to download course material