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EECS 225A

Statistical Signal Processing

3 credits · Graduate

This course connects classical statistical signal processing (Hilbert space filtering theory by Wiener and Kolmogorov, state space model, signal representation, detection and estimation, adaptive filtering) with modern statistical and machine learning theory and applications. It focuses on concrete algorithms and combines principled theoretical thinking with real applications.

Prerequisites & course information

{'preRequisiteCourse': '1543161', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1062941', 'concurrentPrerequisit': False}

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