Open University

Tampere

Vector Space Methods for Signal and Image Processing, Lectures

Contact information Email: open.studies.tau [at] tuni.fi Phone: 0294 520 200More information concerning Open University studies <a href="https://www.tuni.fi/open-university">tuni.fi/open-university</a>

Advanced studies

Faculty of Information Technology and Communication Sciences

Technology and Natural Sciences

Apply for Open University studies by using the following links:<ul><li><a href="https://tau-avoin.ilmoittaudu.fi/lobby/?realization=J-otm-efe85715-c6bb-4284-9a8d-da5fc1a34915_2023-tampere-COMPSGN230" target="_blank">COMP.SGN.230 Vector Space Methods for Signal and Image Processing, lectures, Tampere</a></li></ul>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.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.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.

English

Hervanta Campus

Contact teaching

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>.

<h2>Common</h2><h3>Lecture: </h3>08.01.2024 10:00 - 12:00, TAU P&#228;&#228;rakennus PC110 opetustila Ulan Bator (30) 09.01.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 09.01.2024 14:00 - 15:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 15.01.2024 10:00 - 12:00, TAU P&#228;&#228;rakennus PC110 opetustila Ulan Bator (30) 16.01.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 16.01.2024 14:00 - 15:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 22.01.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SE201 opetustila (33) 23.01.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 23.01.2024 14:00 - 15:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 29.01.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SE201 opetustila (33) 30.01.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 30.01.2024 14:00 - 15:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 05.02.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SE201 opetustila (33) 06.02.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 06.02.2024 14:00 - 15:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 12.02.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SE201 opetustila (33) 13.02.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 13.02.2024 14:00 - 15:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 19.02.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SE201 opetustila (33) 20.02.2024 10:00 - 12:00, TAU S&#228;hk&#246;talo SM207 opetustila (30) 20.02.2024 14:00 - 15:00, TAU S&#228;hk&#246;talo SM207 opetustila (30)

After completing this course, the student will - be able to model and solve signal processing problems through a wide range of vector-space methods - be able to extend the geometrical intuition from familiar 2D and 3D to very high-dimensional settings within a rigorous framework - be able to implement a wide range of fixed and adaptive signal transforms and understand their general properties - master the geometrical structures inherent to basic signal processing techniques, including color transforms, convolution filters, sliding window methods. - be able to design and implement consistent multi-dimensional differential operators for discrete signals - be analyze the propagation of signal distortions (e.g., noise) across transformations

<h5>Material</h5><ul><li>Type:&#160;Lecture slides</li><li>Name:&#160;slides and software examples from the lectures</li><li>Author:&#160;A. Foi</li><li>Exam material:&#160;Yes</li><li>URL:&#160;www.cs.tut.fi/~foi</li><li>Language:&#160;English</li></ul><h5>Material</h5><ul><li>Type:&#160;Journal</li><li>Name:&#160;A unified framework for bases, frames, subspace bases, and subspace frames</li><li>Author:&#160;G. Farneb&#228;ck</li><li>Exam material:&#160;No</li><li>Language:&#160;English</li></ul><h5>Material</h5><ul><li>Type:&#160;Book</li><li>Name:&#160;Frames for undergraduates</li><li>Author:&#160;D. Han et al.</li><li>Exam material:&#160;No</li><li>Language:&#160;English</li></ul><h5>Material</h5><ul><li>Type:&#160;Book</li><li>Name:&#160;A wavelet tour of signal processing: the sparse way</li><li>Author:&#160;S. Mallat</li><li>Exam material:&#160;No</li><li>Language:&#160;English</li></ul>Slides and software examples from the lectures (Matlab &amp;amp; Python), constituting the exam material.Additional reading (articles and books): <ul><li>G. &nbsp;Farneb&#228;ck, &amp;#34;A unified framework for bases, frames, subspace bases, and &nbsp;subspace frames,&amp;#34; Proceedings of the 11th Scandinavian Conference on &nbsp;Image Analysis: Kangerlussuaq, Greenland, 1999, pp. 341-349. &nbsp; &nbsp; &nbsp; &nbsp; </li><li>D. Han et al., Frames for undergraduates, Vol. 40. American Mathematical Soc., &nbsp; &nbsp; &nbsp; 2007.</li><li>S. Mallat, A wavelet tour of signal processing: the sparse way, &nbsp; &nbsp; &nbsp;Academic Press, 2008.</li></ul>

Lectures (including exercises) 4-5 hours per week Attendance &nbsp;to lectures is mandatory (&amp;#61;very strongly recommended). &nbsp;Course &nbsp;assessment and grading is based on written examination.

Vector Space Methods for Signal and Image Processing, Lectures

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Vector Space Methods for Signal and Image Processing, 5 cr

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Vector Space Methods for Signal and Image Processing, Lectures