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Course description

Prediction, smoothing and filtering of 1D signals, with an emphasis on data from mobile devices (e.g. accelerometry, audio, GPS).
Wavelet and Fourier transforms. Convolution and Filtering.
Fundamentals of time series analysis. Dynamic Programming. Hidden Markov Models.
Programming in Matlab or Python.

Logistics

3 credits, Tue. Thu. 10:30-11:45. The first meeting is Tuesday Aug. 25


Staff

Please start the subject of all emails with "CS5660". Thanks!

 

Class forum

  • Discussions can be posted on Piazza

 

Pre-requisites

 Students are expected to have knowledge of Basic Probability Theory and Linear Algebra (here is a list of topics).

Grading and workload

The course will include three programming assignments, due approximately once per month. Currently the due dates are September 29, November 5 and November 26.