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2.687

Time Series Analysis and System Identification

3-0-9 units · Graduate

Covers matched filtering, power spectral (PSD) estimation, and adaptive signal processing / system identification algorithms. Algorithm development is framed as an optimization problem, and optimal and approximate solutions are described. Reviews time-varying systems, first and second moment representations of stochastic processes, and state-space models. Also covers algorithm derivation, performance analysis, and robustness to modeling errors. Algorithms for PSD estimation, the LMS and RLS algorithms, and the Kalman Filter are treated in detail.

Prerequisites & course information

Prereq: 6.3010 and 18.06 G (Fall, Spring) Not offered regularly; consult department 3-0-9 units Can be repeated for credit.

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