Open University

<p>Apply for Open University studies by using the following links:</p><ul><li><a href="https://tau-avoin.ilmoittaudu.fi/lobby/?realization=J-otm-255cf5a4-d0fe-499f-a984-6a3a771237fc_2024-tampere-COMPSGN100" target="_blank">COMP.SGN.100 Introduction to Signal Processing, lectures, Tampere</a></li></ul><p>You can find a link to the Open University Admissions service and application instructions on the <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a> page.</p><p>Some of the studies require prior studies. For example, studying intermediate studies may require some completed basic studies. These are described on the Information about studies tab of the study unit under prior requirements.</p><p>When you have been admitted to the studies, you must enrol separately via the Sisu information system for the implementation of the unit of study and, for example if set, for a practise group of your choice. You will receive instructions on how to do this by e-mail after you have confirmed your acceptance of the study place by paying the required fee.</p>

Tampere

Introduction to Signal Processing, Lectures

<p>The course has two lectures per week. Lectures are on campus and are live streamed and recorded.</p><p>The weekly exercises can be done independently in Moodle and have both mathematical and Matlab Grader tasks. To support the completion of the tasks, classroom exercises are organized on campus (as well as one remote group). Participation in groups is voluntary and there is no registration for them.</p><p>Course exams are organized as both centralized paper exams and electronic exams. However, in each of the three exams, you can only participate in either the paper exam or the electronic exam, but not both.</p><p>Please note that the course has both English and Finnish implementation running simultaneously. Register for only one of these implementations.</p>

<p>Contact information<br>Email: <span class="spamspan"><span class="u">open.studies.tau</span> [at] <span class="d">tuni.fi</span></span><br>Phone: 0294 520 881</p><p>More information concerning Open University studies<br><a href="https://www.tuni.fi/open-university">tuni.fi/open-university</a></p>

Basic studies

Faculty of Information Technology and Communication Sciences

Data Processing and Information Technology

English

Hervanta Campus

Contact teaching

<p>Look information at <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a>.</p>

<h5>Core content</h5><ul><li>Basics of digital signal processing: sampling theorem, discrete signals and their properties,&#160;digital linear systems and their properties and convolution operator.</li><li>Analysis&#160;of linear systems: discrete Fourier transform, FFT &nbsp;algorithm, z-transform, transfer function and frequency response.</li><li>Synthesis of linear systems:&#160;Designing FIR filters using the window design method.</li><li>Multirate DSP: decimation and Interpolation operations.</li><li>Basics of machine learning: nearest neighbor and linear classifiers.</li><li>Example applications and visiting lecture from&#160;the university/industry.</li></ul><h5>Complementary knowledge</h5><ul><li>Fourier transform, Fourier series and Discrete-time Fourier transform</li><li>Design of IIR filters</li><li>Applications of multirate in A/D and D/A conversion.</li></ul><h5>Specialist knowledge</h5><ul><li>Parks-McClellan algorithm</li></ul>

<h2>Common</h2><h3>Lecture: </h3><p>28.08.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>29.08.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>04.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>05.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>11.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>12.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>18.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>19.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>25.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>26.09.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>02.10.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>03.10.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>09.10.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br>10.10.2024 12:00 - 14:00, TAU Festia FA032 Pieni sali 1 (100)<br></p><h2>Groups</h2><h3>Group 1: </h3><p>03.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>10.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>17.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>24.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>01.10.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>08.10.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br></p><h3>Group 2: </h3><p>04.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>11.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>18.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>25.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>02.10.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>09.10.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br></p><h3>Group 3: </h3><p>02.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>09.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>16.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>23.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>30.09.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br>07.10.2024 14:00 - 16:00, TAU Tietotalo TC303 tietokoneluokka (16)<br></p><h3>Group 4: </h3><p>06.09.2024 14:00 - 16:00<br>13.09.2024 14:00 - 16:00<br>20.09.2024 14:00 - 16:00<br>27.09.2024 14:00 - 16:00<br>04.10.2024 14:00 - 16:00<br>11.10.2024 14:00 - 16:00<br></p>

<p>After completing the course, the student can:<br></p><ul><li>recognize the fundamental concepts of signal processing, discuss them and solve problems related to them</li><li>master the basics of Matlab and has obtained the basic calculation routine needed for more advanced courses</li><li>analyze the most important properties of a linear filter through its transfer function</li><li>design an FIR filter both by Matlab and by hand using the window design method</li><li>calculate the discrete Fourier transform of a sequence both by the matrix method and the FFT algorithm</li><li>design a linear classifier both by hand and with Matlab.</li></ul>

Finnish

<h2>Prerequisites</h2><p>Knowledge corresponding to compulsory prerequisites obtained in other means is also valid.</p><h2>Compulsory Prerequisites</h2><ul><li>Introductory Calculus, MATH.APP.111, 5 cr</li><li>Vectors and Matrices, MATH.MA.140, 5 cr</li></ul><h2>Recommended Prerequisites</h2><ul><li>Signals and Measurements, EE.010, 5 cr</li></ul>

<ul><li>AYBIODIVO Open University Route, Biotechnology and Biomedical Engineering, MSc</li><li>AYBSEMSCVO Open University Route, Biomedical Sciences and Engineering, MSc</li></ul>

<h5>Material</h5><ul><li>Type: Lecture handout<br></li><li>Name: Introduction to Signal Processing</li><li>Author: Sari Peltonen<br></li><li>Exam material:&#160;Yes</li><li>Language: English</li></ul>

Introduction to Signal Processing, Lectures

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