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ENGR207 HM - Digital Signal Processing: Theory & Application


Credit(s): 3

Instructor(s): Staff

Offered: Spring

Description: Deterministic and probabilistic signal processing of data in time and frequency domain. Students will be able to use various tools and concepts to process signals. These may include: Discrete Fourier transform, short time Fourier transform, dynamic time warping, probability and random variables, hidden Markov models, Gaussian Markov models, instantaneous frequency estimation, phase vocoder, and non-negative matrix factorization. Students will also develop the programming skills to build signal processing systems in practice.

Prerequisite(s): ENGR101 HM  and CSCI060 HM , or permission of instructor.