EGR-2050 — Signals and Systems: Modeling, Computation, and Analysis
Solving high-level applications in engineering, physics, chemistry, and biology require an understanding of modeling at a system level. To fully prepare a student, this course emphasizes system analysis. Crucial to modeling in the modern world is an understanding of the computational modeling as well as the mathematical formulation, therefore a variety of numerical/computational methods will be reviewed in the first part of the course and extended for the purpose of understanding the computational methods required to do modeling in a modern setting. Subjects to be studied include error analysis, roots of non-linear equations, solving systems of linear equations, eigenvalues, eigenvectors, and eigenfunctions, optimization, curve fitting including splines, Fourier analysis, modeling, numerical differentiation and integration, and numerical solving of differential equations including, but not limited to, predictor-corrector methods and finite element analysis. It will be assumed that the student is at least partially familiar with these concepts from previous mathematics class. Extra study may be required for a student lacking these skills. These concepts will be extended into computational methods that are useful in analyzing signals and systems. Topics will include representation of systems and signals, transfer functions, and filters. The relationship between linear systems and both discrete time and continuous time signals and sampling will be explored and used to better und
Prerequisites: EGR-1010, EGR-1140, MAT-2420