Signals and Systems: Modeling, Computation, and Analysis at Prince George's Community College
Prince George's Community College: EGR 2050: Signals and Systems: Modeling, Computation, and Analysis (formally Introductory Numerical Methods)
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 this 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 understand real world applications. Practical issues of representation
and sampling of signals will be explored with particular emphasis to best case solutions.
This will be extended in to the study and use of a number of filters, in particular digital filters.
Topics will include OTFs, DFTs, Laplace transforms, Z-transforms, Radon transforms, and convolutions.
Lastly, there will be extensive surveys of a number of advanced subjects include molecular dynamics, percolation,
and Monte Carlo simulation methods. Some new mathematical concepts will be introduced in the class.
A number of software packages and languages important to engineering are surveyed with primary emphasis
on mastering one high-level language such as MATLAB/Octave, C/gcc/g++, or Fortran/gfortran.
This course, recognizing the fact that all engineers and scientists need the aforementioned topics,
will emphasize a number of case studies in such areas as mechanical, civil, environmental, electrical,
aerospace, chemical, and biological engineering, as well as in the sciences.
Team work along with communication skills (oral, written, and graphical) are exercised throughout the course.
Prerequisite: EGR 1010, EGR 1140, and MAT 2420.
4 Credits (class/design/lab)
3rd Edition. Hamming, R. W. Dover Publications, Inc. New York (1989).
A First Course in Numerical Analysis
2nd Edition. Ralston, A. & Rabinowitz, P. Dover Publications, Inc. New York (1978).
Schaum's Outline of Signals and Systems
Schaum's Outline of Numerical Analysis
Schaum's Outline of Finite Element Analysis
Writing in Engineering.
Oxford University Press (2016).
Numerical Methods for Scientists and Engineers 2nd Edition.
Hamming, R.W. Dover Publications,
Inc. New York (1986).
-- This book is a classic for numerical methods.
Numerical Solution of Differential Equations. Milne, W.
E. Dover Publications, Inc. New York (1970). -- This may only be available in a used book store.
Matlab/Octave Classroom discussion (under clean-up, but available; under construction)
Matlab Tutorials and Programs (under construction always)
Ovtave information (under construction)