| TBMI26 | Neural Networks and Learning Systems, 6 ECTS credits. /Neuronnät och lärande system/ |
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Prel. scheduled
hours: 56 |
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Area of Education: Technology Main field of studies: Biomedical Engineering, Electrical Engineering |
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| Advancement level
(G1, G2, A): A
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| Aim: The aim is that students after passing the course will be able to design and apply artificial neural networks and other learning systems for adaptive data analysis. Students will also be able to apply such methods in order to find meaningful relations in multidimensional signals where the degree of complexity makes traditional model-based methods unsuitable or impossible to use. Specifically, students should be able to:
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| Prerequisites: (valid for students admitted to programmes within which the course is offered) Requisite: Algebra, Multivariable Calculus, Mathematical statistics. Recommended: Signal theory. Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding. |
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| Organisation: Lectures, Exercises, Laboratory exercises (including an obligatory written report) |
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| Course contents: Classification: pattern recognition, discriminant functions; Supervised learning: the perceptron, the multi-layer perceptron, stochastic gradient search, error back-propagation; Unsupervised learning: principal component analysis (PCA), canonical correlation analysis (CCA), independent component analysis (ICA), competitive learning, self organizing maps (SOM), clustering; Content addressable memories: state spaces, Hopfield memories; Reinforcement learning: Markov models, Q-learning; Genetic methods: genetic algorithms, genes and schemas |
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| Course literature: S. Haykin, Neural Networks, second edition, Prentice Hall 1999 Compendium: examples, supplementary material, lab manual |
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| Examination: | |||
| Written examination Laboratory work |
4 ECTS 2 ECTS |
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Course language is Swedish/English. Department offering the course: IMT. Director of Studies: Håkan Örman Examiner: Magnus Borga Link to the course homepage at the department Course Syllabus in Swedish |
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