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EE 103: Introduction to Matrix Methods (CME 103)

Introduction to applied linear algebra with emphasis on applications. Vectors, norm, and angle; linear independence and orthonormal sets. Matrices, left and right inverses, QR factorization. Least- squares and model fitting, regularization and cross-validation, time-series prediction, and other examples. Constrained least-squares; applications to least-norm reconstruction, optimal control, and portfolio optimization. Newton methods and nonlinear least-squares. Prerequisites: MATH 51 or CME 100.
Terms: Aut | Units: 4-5 | UG Reqs: GER:DB-Math, WAY-FR
Instructors: Boyd, S. (PI)
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