Digital Signal Processing II

Course Number: 
SIO 207C
Course Description: 
Adaptive filter theory, estimation errors for recursive least squares and gradient algorithms, convergence and tracking analysis of LMS, RLS, and Kalman filtering algorithms, comparative performance of Wiener and adaptive filters, transversal and lattice filter implementations, performance analysis for equalization, noise canceling, and linear prediction applications. (Recommended Prerequisites: ECE251A or ECE 251AN.)
Prerequisites: 
graduate standing ECE 251A (for ECE 251B); SIO 207B (for SIO 207C).
Number of Units: 
4
Academic Year: 
2012-2013
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