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MREN 223 Signals and Systems Units: 4.00
This course covers the basic concepts and techniques for the modeling and analysis of signals and systems. Topics include signals, system properties, linear time-invariant systems, convolution, impulse response in continuous-time and discrete-time domains; Fundamentals of Fourier series; Fourier transforms, spectral analysis; Laplace transforms, and frequency response; sampling, reconstruction, and digitization; z transform and frequency response; fundamental concepts of filtering in continuous-time and discrete-time domains; Computational realizations of the analysis tools and their applications are explored in the laboratory.
(Lec: 3, Lab: 0.5, Tut: 0.5)
(Lec: 3, Lab: 0.5, Tut: 0.5)
Offering Term: W
CEAB Units:
Mathematics 12
Natural Sciences 0
Complementary Studies 0
Engineering Science 36
Engineering Design 0
Offering Faculty: Smith Engineering
Course Learning Outcomes:
- Classify systems based on their properties: in particular, to understand and exploit the implications of linearity, time-invariance, causality, memory, and bounded-input, bounded-out (BIBO) stability.
- Apply the concepts of convolution, impulse response and transfer function to linear time-invariant systems.
- Determine, interpret and plot Fourier transform magnitude and phase for continuous- and discrete-time functions.
- Apply Laplace transform and its inverse to solve differential equations and to determine the response of linear time-invariant systems to known inputs.
- Use Z transform and its inverse to solve difference equations and to determine the response of linear time-invariant systems to known inputs.
- Derive the Fourier Transforms and use it as a tool for frequency-domain analysis.
- Simulate signals and systems using modern computer software packages.
- Use linear systems tools, especially transform analysis and convolution, to analyze and predict the behavior of linear systems.
- Investigate sampling theorem, aliasing and eth effect of quantization.