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MECE E6620y Applied Signal Recognition and Classification
Lect: 3. 3pts. Professor Beigi.
Prerequisite: MATH E1210, APMA E3101, programming,
or permission of the instructor.
Applied recognition and classification of signals using a selection of tools
borrowed from different disciplines. Applications include human biometrics,
imaging, geophysics, machinery, electronics, networking,
languages, communications, and finance. Practical algorithms are
covered in signal generation, modeling, feature extraction,
metrics for comparison and classification,
parameter estimation, supervised, unsupervised and hierarchical clustering and
learning, optimization, scaling and alignment,
signals as codes emitted from natural sources,
information, markov modeling, and extremely large-scale search techniques.
Homayoon S.M. Beigi
2003-12-12