ECE 30100 - Signals and SystemsLecture Hours: 3 Credits: 3
Normally Offered: Each Fall, Spring, Summer
(ECE 20002 Minimum Grade of C or ECE 20200 Minimum Grade of C or BME 30500) and (MA 26200 or MA 36600 or MA 26600)
Classification, analysis and design of systems in both the time- and frequency-domains. Continuous-time linear systems: Fourier Series, Fourier Transform, bilateral Laplace Transform. Discrete-time linear systems: difference equations, Discrete-Time Fourier Transform, bilateral z-Transform. Sampling, quantization, and discrete-time processing of continuous-time signals. Discrete-time nonlinear systems: median-type filters, threshold decomposition. System design examples such as the compact disc player and AM radio.
To develop the analytical tools and techniques needed for the design and analysis of discrete-time and continuous-time linear systems - convolution, transforms, and sampling theory are therefore the primary topics.
- Signals and Systems, 2nd Edition, Oppenheim, Willsky, and Hamid, Prentice-Hall, 1996, ISBN No. 9780138147570.
- MatLab: Student Version, Current Edition, The MathWorks, Inc..
Learning Outcomes:A student who successfully fulfills the course requirements will have demonstrated:
- an ability to classify signals (e.g. periodic, even) and systems (e.g. causal, linear) and an understanding of the difference between discrete and continuous time signals and systems. 
- an ability to determine the impulse response of a differential or difference equation. 
- an ability to determine the response of linear systems to any input signal by convolution in the time domain. 
- an understanding of the definitions and basic properties ( e.g. time-shift, modulation, Parseval's Theorem) of Fourier series, Fourier transforms, bilateral Laplace transforms, Z transforms, and discrete time Fourier transforms and an ability to compute the transforms and inverse transforms of basic examples using methods such as partial fraction expansions. 
- an ability to determine the response of linear systems to any input signal by transformation to the frequency domain, multiplication, and inverse transformation to the time domain. 
- an ability to apply the Sampling theorem, reconstruction, aliasing, and Nyquist's theorem to represent continuous-time signals in discrete time so that they can be processed by digital computers. 
|3||Systems design tasks and tool, system classifications|
|6||Time-domain solution of difference equations|
|5||Discrete-time impulse responses and convolution|
|4||Sums of sinusoids and the Fourier Series|
|5||The Fourier Transform and its properties, transfer functions|
|3||Sampling and quantization|
|4||Discrete-Time Fourier Transform and its properties|
|2||Discrete-time processing of continuous-time signals|
|5||The bilateral z-Transform and its properties|
|3||The bilateral Laplace Transform and its properties|
|2||System design examples|