ECE269: Linear Algebra and Applications

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Course description

Mathematical foundation of linear algebraic techniques and their applications in signal processing, communication, and machine learning. Geometry of vector and Hilbert spaces, orthogonal projection, systems of linear equations, the role of sparsity, eigenanalysis, Hermitian matrices and variational characterization, positive semidefinite matrices, singular value decomposition, and principal component analysis.

Prerequisite

Undergraduate linear algebra at the level of Math 18 or 20F. Working knowledge of mathematics. These prerequisites should be taken very seriously.

Course requirements and grading

Lectures

Teaching staff