CNS/EE
148 - Spring 2000
Background material
Probability
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Random variable, probability density function, expectation, moments.
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Gaussian random variable.
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Independent variables. Conditional probability density function.
Bayes' rule (reviewed in class).
Linear algebra
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Vector, matrix, product.
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Basis of a linear space. Change of basis.
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Eigenvalues, eigenvectors.
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Representing rotations and other linear transformations with matrices.
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Singular value decomposition (reviewed in class).
Signal processing and linear systems
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Convolution, correlation.
Matlab
Some familiarity. Make sure that you have a computer account from which
you can run Matlab (e.g. ITS).
Matrix-vector product. Plot a function. Load and display an image.
Run convolution.
Highly recommended to go through the brief tutorial.
Last
updated: March 10, 2000.