Courses

Covers development, computer implementation, and analysis of numerical methods for applied mathematical problems. Topics include floating point arithmetic, numerical solution of linear systems of equations, root finding, numerical interpolation,differentiation, and integration. Prerequisites: Requires prerequisite courses of CSCI 1300 and APPM 1350 or MATH 1300 and APPM 1360 or MATH 2300 and MATH 3130 or APPM 3310 (all minimum grade C-).
Explores chaotic dynamics theoretically and through computer simulations. Covers the standard computational and analytical tools used in nonlinear dynamics and concludes with an overview of leading-edge chaos research. Topics include time and phase-space dynamics, surfaces of section, bifurcation diagrams, fractal dimension, and Lyapunov exponents. Recommended prereqs., PHYS 1120, CSCI 3656, and MATH 3130. Same as CSCI 5446 and ECEN 4423. Prerequisites: Requires prerequisite course of CSCI 1300 and APPM 2350 or MATH 2400 (all minimum grade C-).

Introduces computing systems, software, and methods used to solve large-scale problems in science and engineering. Students use high-performance workstations and a supercomputer. First course in a two-semester sequence. Recommended prereq., CSCI 3656. Same as CSCI 5576.

Introduces computing systems, software, and methods to solve large-scale problems in science and engineering. Students use high-performance workstations and a supercomputer. Second course in a two-semester sequence. Prerequisites: Requires prerequisite course of CSCI 4576 (minimum grade D-).
Same as CSCI 4446 and ECEN 5423. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree (CSEN) majors only.
Same as CSCI 4576. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree (CSEN) majors only.
Highlights computer arithmetic, solution of linear systems, least-squares approximations, nonlinear algebraic equations, interpolation, and quadrature. Recommended prereqs., CSCI 3656 and three semesters of calculus, or equivalent. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree (CSEN) majors only.
Focuses on finite difference solution for partial differential equations, methods of SoR, ADI, conjugate gradients, finite element method, nonlinear problems, and applications. Prerequisites: Requires prerequisite course of CSCI 5606 (minimum grade D-). Restricted to graduate students or Computer Science Concurrent Degree (CSEN) majors only.
Offers direct and iterative solutions of linear systems. Also covers eigen value and eigenvector calculations, error analysis, and reduction by orthogonal transformation. A sound knowledge of basic linear algebra, experience with numerical computation, and programming experience is required. Prerequisites: Restricted to graduate students or Computer Science Concurrent Degree (CSEN) majors only.
Looks at modern computational methods for solution of unconstrained optimization problems, nonlinear leastsquares, and systems of nonlinear equations. Techniques for building algorithms to solve problems with special structure. Prerequisites: Requires prerequisite course of CSCI 5606 (minimum grade D-). Restricted to graduate students only.
Covers computational methods for constrained optimization. Topics include basic theory, methods for quadratic programming, active set strategies for linear constraints, and penalty and successive quadratic programming methods for nonlinearly constrained problems. Prerequisites: Requires prerequisite course of CSCI 5606 (minimum grade D-). Restricted to graduate students only.
Topics selected by instructor. Possible topics are numerical linear algebra, solution of differential equations, nonlinear algebra and optimization, data fitting, linear and nonlinear programming, and solution of large problems. Department consent required. Prerequisites: Restricted to graduate students only.