EECE 7219 - Pattern Recognition

Credit Hours: 3

Description Geometry of Euclidean space, vector spaces and subspaces, linear independence, linear transformations, eigenvalues and eigenvectors, decision theory, density estimation, dimensionality reduction, statistical classification and clustering, hidden Markov models, manifold learning, statistical learning theory, and ensemble learning. Engineering PREREQUISITE(S): Basic knowledge of Linear Algebra, Probability and Statistics, and Programming experience in a high level programming language (C/C++/MATLAB etc.) is required or permission by the instructor.