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Applied Mathematics for Cognitive Science (Lecture + Tutorial)

8.3406

Dozenten

Beschreibung

Topics to be Covered:
1. Selected Topics in Probability & Information Theory from: Basics of Probability, Bayes’ Theorem & Inference, Shannon Information content of a Random Variable, Entropy & Mutual Information, Kullback-Leibler Divergence, Law of Large Numbers, Coding, Data Compression & Typicality, Monte Carlo Methods.
2. Selected Topics in Fourier Analysis from: Fourier Series, One-dimensional Wave, Fourier Transforms - Continuous, Discrete, Discrete-time & their properties, Convolution in Signal Processing and Filters.
3. Selected Topics in Mathematical Programming from: Geometrical Approach, Simplex Method, Duality, Lagrangian Multipliers.
4. Selected Topics in Dynamical Systems Theory from: Linear systems in one- and two-dimensions, Phase Plane analysis, Bifurcations - Saddle-node, Transcritical, Pitchfork.
5. Miscellaneous Topics from: Approximation by Polynomials - Taylor Series, Principal Component Analysis, Laplace Transforms, Hebbian Learning, Metric Spaces.

Weitere Angaben

Ort: 32/107: Di. 10:00 - 12:00 (13x), HS - SL 203: Mi. 14:00 - 16:00 (9x), 32/106: Mi. 14:00 - 16:00 (4x)
Zeiten: Di. 10:00 - 12:00 (wöchentlich) - Tutorial & Practice, Ort: 32/107, Mi. 14:00 - 16:00 (wöchentlich) - Lecture, Ort: HS - SL 203, 32/106
Erster Termin: Mi , 03.04.2019 14:00 - 16:00, Ort: HS - SL 203
Veranstaltungsart: Vorlesung (Offizielle Lehrveranstaltungen)

Studienbereiche

  • Cognitive Science > Bachelor-Programm