| Type: | Open University
Language: English |
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Previous course: C4213
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No credit points with: C4213
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Prerequisite: 04361/04362 /C4232
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Recommended semester: 7th - 9th semester
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Scope and form: Lectures, mandatory computer exercises and homework problems.
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Examination: Oral exam. Approval of compulsory coursework is a prerequisite for taking part in the exam. (13-scale)
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Remarks: This course forms together with course 04365 and 04461, 04462 advanced courses in the area of digital signal processing. The corresponding introductory course is 04361 and 04362.
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Department: Informatics and Mathematical Modelling
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Aim: To provide the student with a basis for developing algorithms and planning digital systems with emphasis on non-linear signal processing. The signals can be of many types, but the course will mainly deal with speech signals and biomedical signals.
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Contents: The lectures will be chosen among the following topics: Neural Networks. An introduction to the theory of neural networks is given. The theory will be illustrated by applications in a number of areas, including the biomedical area. Speech Coding. The point covers an introduction to the principles of speech coding with emphasis on coding at low bit rates (< 10 KBPS). The theory will be illustrated by applications in the areas of multimedia, telecommunication and aids for the handicapped. Speech Recognition. The point includes methods for recognition of speech, especially methods based on Hidden Markov Models and/or neural networks. Applications are equivalent to the topics mentioned above, multimedia, telecommunication and aids for the handicapped. Vector Quantization. Vector quantization is a general discipline for effective coding of signals, including speech signals and biomedical signals. Pattern Recognition. Bayesian decision theory and mathematical modelling of pattern recognition systems.
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