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 2016.
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 online tutorials (http://imaging.mrccbu.cam.ac.uk/meg/Beginners).
To hear more about skillsoriented training opportunities at the CBU, please register on this mailing list: http://lists.mrccbu.cam.ac.uk/mailman/listinfo/skillstraining (NonCBU people can subscribe by sending an email to skillstrainingsubscribe (at) mrccbu (dot) cam (dot) ac (dot) uk).
You may want to have a look at other skillsoriented 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.
The documents/scripts attached to future workshops in the schedule below are still from last year, and will be updated in due course.
Date 
Topic 
Tutor 
Jan 25 
Sampling, Signals, Noise Sampling rate, aliasing, signaltonoise ratio, error propagation,PDF 
Alessandro Tomassini 
Feb 1 
Introduction to Matrix Algebra Vectors, matrices, and what you can do with them,PDF 
Alessandro Tomassini 
Feb 8 
The general linear model I Linear equations, matrix inversion PDF 
Amy Johnson 
break 


Feb 22 
The general linear model II PCA and SVD, analysing linear equations, eigenvalues and singular values, stability of linear estimators PDF, M 
Rezvan Farahibozorg 
Mar 1 
Functions and calculus properties of some common functions, polynomials etc., derivation and integration PDF, M 
Pei Huang 
Mar 8 
Filtering and oscillations Properties of sine and cosine functions, FFT, filtersPDF, M 
Darren Price 
Mar 15 
Optimisation Principles of linear and nonlinear optimisation PDF, M 
Darren Price 