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Course Criteria
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1.00 Credits
Math 341/COSC 341/CPMA 541 Working Group in computational Mathematics Seminar Style course serving as a forum in which students and faculty discuss research topics of current interest. Each working group will consist of a combination of faculty lectures, student presentations. Open discussions, and group projects. Student participants will be expected to lead at least one class discussion. The content of the course will vary from term to term.
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3.00 Credits
Network technologies, protocols, and management. Programming networked applications. The effects of the Internet and World Wide Web on computing and society.
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3.00 Credits
Introduction to the mathematics of images and image processing, as well as computational methods for real data manipulation. Topics include image acquisition, image enhancement and restoration in both the spatial and frequency domains, the Fourier transform, wavelets, image compression, image segmentation, and morphological processing algorithms.
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3.00 Credits
Graph theory, graph algorithms, coloring, network flows, computational geometry, compression, randomized algorithms, parallel algorithms, and NP-completeness.
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3.00 Credits
Option strategies, future markets, option price relations, binomial option pricing model, binomial put model, and the Black-Scholes analysis.
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3.00 Credits
Mathematical techniques for securing data for storage or transmission in an insecure context: abstract algebra, threat modeling, information and coding theory, error-correcting codes, public and private key encryption schemes, and crypt-analytic techniques.
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3.00 Credits
Linear systems, interpolation, functional approximation, numeric differentiation and integration, and solutions to non-linear equations.
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3.00 Credits
This is an introduction to the background of operations including example problems and a brief history. An extensive discussion of the theory and applications of linear programming will follow. Other topics will include integer programming, transportation and network flow models, and dynamic programming.
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3.00 Credits
Linear programming, transportation problem, network flow, nonlinear convex programming, dynamic programming, geometric programming, game theory, and gradient methods.
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3.00 Credits
Regression algorithms, simulation, generating pseudo-random numbers, Markov chain Monte Carlo, and the bootstrap.
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