Advice on writing projects/reports

I have seen too many bad reports and I find myself writing the same advice over and over again. Any student writing a lab, thesis, exam, or assignment should at least peruse the following:

Past Semesters

 Winter 2017

  • SD332 - Earth Systems Course Times: Mondays 2:30p.m to 4:00p.m, Thursdays 2:30p.m to 4:00p.m

    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.

Fall 2015

  • SD770 - Statistical Image Processing:

    Course Times: Tuesdays, Thursdays 10:00a.m to 11:30a.m, 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.

Winter 2009

  • SD372 - Pattern Recognition:

    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.

  • SD675 - Pattern Recognition:

    Course Times: Mondays, Wednesdays, 10:30a.m to 11:50a.m, E2-1307C

    The course starts with a brief summary of SYDE 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.

Fall 2005

  • SD252 - Signals & Systems:

    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.

Courses I No Longer Teach

  • SD192 - Digital Systems:

    Digital technology, combinatorial logic, binary arithmetic, synchronous sequential circuits, design methodology, algorithmic state machines, microcomputer interfacing.