Welcome to Course 31561 - Applied Signal Processing

This web site is under construction and will first be finished at the start of the semester

Welcome to the home page of the course 31561 - Applied Signal Processing. In this home page, you can find information about the course. You can see both the course plan for the spring 2018, the data for the different exercises and assignments, and various programs used for demonstrations during the lectures. Content will be added to the web-site as the course evolves, and plans might change.

The lectures this year will be given in building 306, auditorium 38 on Mondays and Thursdays. Exercises are performed in the E-databar in building 308, Room Number 001 on seven Mondays (see the course plan for details). On Thursdays after the lecture, there are group work sessions with assignments (12 in total) in the group room 040 in building 324. Refer the course plan for detailed schedule. Tutors will be present for both these activities.

Aim: The purpose of the course is to give the students a solid basis for analysis and processing of analog and digital signals emanating from either deterministic or stochastic system. The major emphasis is on signal examples from the medical world, and practical introduction to analysis and processing of signals is given through computer demonstrations and exercises. The program MATLAB is used for the exercises in combination with different signals from the medical word (e.g. ECG and medical ultrasound). The main emphasis is here on stochastic signals. The (7) lab projects are made in groups of two. Each student should submit (online) 7 reports for grading. The report should be submitted on the Friday (same week) after the lab session. A second chance will be given for re-submission if the report is not satisfactory. The project work will be considered for the final grade. The course is concluded with a final written examination (open book).

Evaluation: The grading of the course is based on two mandatory components:

1. Final (4 hours) written examination, and
2. Seven (7) project (computer lab) reports.

Contents: Classification of signals. Analytic signals. Use of the fast Fourier transform (FFT). Analysis of stochastic signals. Correlations functions, power and cross spectra. Errors in analog to digital conversion. Digital filters and their error sources. Matched filter. Spectral estimation. Parametric models. Use of signal processing software (Matlab). Processing of biomedical signals. Digital signal processors. Exercises. Signal processing assignment.

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