ECE 30100 - Signals and Systems

Course Details

Lecture Hours: 3 Credits: 3

Counts as:

  • EE Core
  • CMPE Core

Normally Offered:

Each Fall, Spring, Summer


On-campus and online


(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)

Catalog Description:

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.

Course Objectives:

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.

Required Text(s):

  1. Signals and Systems , 2nd Edition , Oppenheim, Willsky, and Hamid , Prentice-Hall , 1996 , ISBN No. 9780138147570

Recommended Text(s):

  1. MatLab: Student Version , Current Edition , The MathWorks, Inc.

Learning Outcomes:

A student who successfully fulfills the course requirements will have demonstrated:
  1. 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. [1]
  2. an ability to determine the impulse response of a differential or difference equation. [1]
  3. an ability to determine the response of linear systems to any input signal by convolution in the time domain. [1]
  4. 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. [1]
  5. 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. [1]
  6. 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. [1]

Lecture Outline:

Lectures Topic(s)
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
3 Tests

Assessment Method: