Counts as:

• EE Core
• CMPE Core

Normally Offered:

Each Fall, Spring, Summer

Campus/Online:

On-campus and online

Requisites:

(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.

Learning Outcomes:

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:

Assessment Method:

none