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||Jan 21 ||'''Introduction to Matrix Algebra''' ''Vectors, matrices, and what you can do with them'' || ||Jan 21 ||'''Introduction to Matrix Algebra''' ''Vectors, matrices, and what you can do with them'' [[attachment:EMEGdata.mat|Example data]] [[attachment:MatrixAlgebra.m|Matlab examples]] ||
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Introduction to Signal Analysis In Matlab

Below you will find the schedule of our “Introduction to Signal Analysis In Matlab” workshops, held in the CBSU West Wing Seminar Room on Wednesdays, 11.00, between January and March 2015.

Matlab is the Swiss Army Knife of data analysis: no matter whether you are analysing neuroimaging data, behavioural data or your latest bank statements, Matlab can make you do things you thought were never possible.

These workshops are aimed at beginners, but some basic knowledge of Matlab is required, e.g. at the level of our previous "Introduction to Matlab and Scientific Computing" workshops (materials available here). We are not intending to provide a full Matlab or signal processing course, but we hope we can significantly facilitate the first few steps. For other options, see e.g. opportunities at Cambridge University (http://training.cam.ac.uk/ucs/), or on-line tutorials (http://imaging.mrc-cbu.cam.ac.uk/meg/Beginners).

To hear more about skills-oriented training opportunities at the CBU, please register on this mailing list: http://lists.mrc-cbu.cam.ac.uk/mailman/listinfo/skillstraining (Non-CBU people can subscribe by sending an e-mail to skillstraining-subscribe (at) mrc-cbu (dot) cam (dot) ac (dot) uk).

You may want to have a look at other skills-oriented training options.

Any suggestions of feedback on our previous lectures would be very welcome.

All sessions will take place in the West Wing Seminar Room, on Wednesdays at 11am, and will take approximately 1 hour.

Date

Topic

Jan 14

Sampling, Signals, Noise Sampling rate, aliasing, signal-to-noise ratio, error propagation PDF, M

Jan 21

Introduction to Matrix Algebra Vectors, matrices, and what you can do with them Example data Matlab examples

Jan 28

The general linear model I Linear equations, matrix inversion

Feb 4

The general linear model II PCA and SVD, analysing linear equations, stability

Feb 18

Functions and calculus properties of some common functions, polynomials etc., derivation and integration

Feb 25

Filtering and oscillations Properties of sine and cosine functions, FFT, filters

Mar 4

Optimisation Principles of linear and non-linear optimisation

None: SignalAnalysisMatlabSchedule (last edited 2019-11-21 17:37:44 by OlafHauk)