Welcome to the course webpage |
COURSE DESCRIPTION | |
AIM: | This course provides analytical tools for studying random phenomena in biomedical systems. Special emphasis is given to properties of random processes. |
LEARNING OUTCOMES: | See course curriculum for detailed intended learning outcomes. |
STYLE AND ASSESSMENT: | Each lecture is 4 hours: Classroom lectures for 2 h and exercises for 2 h. |
EVALUATION: | 3 hours written examination. |
MAIN LITERATURE: | Barkat, Mourad - Signal detection and estimation (2nd Edition) |
COURSE PLAN AND MATERIALS |
Lecture | Lecturer | Topic and Materials | Literature | Learning Expectation |
---|---|---|---|---|
Lecture 1 | Ernest Nlandu Kamavuako | Introduction to probability and random variables Slides | Exercises | Solutions |
Mourad - Page: 1-8; 12-22 | Deep Learning |
Lecture 2 | Ernest Nlandu Kamavuako | Moments and multi-dimensional random variables Slides | Exercises | Solutions |
Mourad - Page: 23-64 | Deep Learning |
Lecture 3 | Ernest Nlandu Kamavuako | Introduction to random processes and stationarity Slides | Exercises | Solutions |
Mourad - Page: 88-96; 141-152 | Deep Learning |
Lecture 4 | Ernest Nlandu Kamavuako | Properties of correlation functions Slides | Exercises | Solutions |
Mourad - Page: 153-155 | Deep Learning |
Lecture 5 | Samuel Schmidt | Some random processes Slides | Exercises | Solutions |
Mourad - Page: 156-173 | Basic Knowledge |
Lecture 6 | Samuel Schmidt | Power spectral density Slides | Exercises | Solutions |
Mourad - Page: 174-178 Biomedical Signal Analysis: A Case-Study Approach |
Deep Learning |
Lecture 7 | Samuel Schmidt | Linear time-invariant systems (Filtering) Slides | Exercises | Solutions |
Mourad - Page: 178-185 | Deep Learning |
Lecture 8 | Samuel Schmidt | Ergodicity Slides | Exercises | Solutions |
Mourad - Page: 186-188 | Deep Learning |
Lecture 9 | Self Study |
Facilitation | ||
Lecture 10 | Ernest Nlandu Kamavuako Samuel Schmidt |
Exam simulation Exam set| Solutions |
Facilitation |
EVALUATION | |
Written (3 hours): The problems of the exam are similar to the exercises done during the course. Thus we recommend that you understand the exercises and solutions and be able to reflect on them. | |
SMI, Fredrik Bajers Vej 7 D3, DK-9220 Aalborg, Denmark, Tel: +45 9940 8827, Fax: +45 9815 4008, E-mail: Contact-SMI | | |