Dept. of Systems Design Engineering
Faculty of Engineering
University of Waterloo
Canada N2L 3G1
Tel: (519) 888-4567 x84970
FAX: (519) 746-4791
A broad, overview course introducting students to aspects of the Engineering and Mathematics principles associated with the earth as a system. The course will look as aspects of nonlinear systems, partial differential equations, the physics of earth observation, and inverse problems. The emphasis will be on broad, high-level concepts.
Course Times: Tuesdays, Thursdays 10:00-11:30, E5-6002
Not a course in image processing per se; rather it is a course which will study the statistical modeling, analysis, and numerical methods of data processing, especially multidimensional data processing. The course will begin with an overview of inverse problems, ill-posedness, estimation theory, and Kalman filtering.
Pattern recognition as a process of data analysis. Pattern features as components in a random vector representation. Classification techniques: distance measures in feature space, probabilistic decision theory, linear discriminants. Clustering and feature extraction. Applications: optical character recognition, speech recognition, robot vision, medical diagnosis, remote sensing.
Course Times: Mondays, Wednesdays, 10:30-11:50, E2-1307C
The course starts with a brief summary of SY DE 372: probabalistic classifiers, discriminant functions, unlabeled clustering, and feature extraction. More advanced topics will include some information theory (as it pertains to feature extraction), statistical estimation and error analysis (relating to parameter estimation), neural networks, self-organizing maps, and syntactical/grammatical pattern recognition.
Models and analysis of linear systems. Discrete time systems, continuous time systems; difference and differential equations; impulse and frequency response. Complex frequency, functions of complex variables, transform domain techniques: Z transforms; Fourier analysis, Laplace transform. Transfer functions and frequency response, frequency domain analysis of linear systems; sampling theory, stability, and linear filters.
Digital technology, combinatorial logic, binary arithmetic, synchronous sequential circuits, design methodology, algorithmic state machines, microcomputer interfacing.
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