(New page: =Summary of Information for the Final= ==ABET Outcomes== :(a) an ability to classify signals (e.g. periodic, even) and systems (e.g. causal, linear) and an understanding of the difference ...) |
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=Summary of Information for the Final= | =Summary of Information for the Final= | ||
==ABET Outcomes== | ==ABET Outcomes== | ||
| − | :(a) an ability to classify signals (e.g. periodic, even) and systems (e.g. causal, | + | :(a) 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;a] |
| − | linear) and an understanding of the difference between discrete and | + | :(b) an ability to determine the impulse response of a differential or difference equation. [1,2;a] |
| − | + | :(c) an ability to determine the response of linear systems to any input signal convolution in the time domain. [1,2,4;a,e,k] | |
| − | :(b) an ability to determine the impulse response of a differential or difference | + | :(d) an understanding of the deffnitions and basic properties (e.g. time-shifts,modulation, Parseval's Theorem) of Fourier series, Fourier transforms, bi-lateral Laplace transforms, Z transforms, and discrete time Fourier trans-forms and an ability to compute the transforms and inverse transforms of basic examples using methods such as partial fraction expansions. [1,2;a] |
| − | equation. [1,2;a] | + | :(e) 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. [1,2,4;a,e,k] |
| − | :(c) an ability to determine the response of linear systems to any input signal | + | :(f) an ability to apply the Sampling theorem, reconstruction, aliasing, and Nyquist theorem to represent continuous-time signals in discrete time so that they can be processed by digital computers. [1,2,4;a,e,k] |
| − | convolution in the time domain. [1,2,4;a,e,k] | + | |
| − | :(d) an understanding of the deffnitions and basic properties (e.g. time-shifts, | + | |
| − | modulation, Parseval's Theorem) of Fourier series, Fourier transforms, bi- | + | |
| − | lateral Laplace transforms, Z transforms, and discrete time Fourier trans- | + | |
| − | forms and an ability to compute the transforms and inverse transforms of | + | |
| − | basic examples using methods such as partial fraction expansions. [1,2;a] | + | |
| − | :(e) 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. [1,2,4;a,e,k] | + | |
| − | :(f) an ability to apply the Sampling theorem, reconstruction, aliasing, and | + | |
| − | Nyquist theorem to represent continuous-time signals in discrete time so | + | |
| − | that they can be processed by digital computers. [1,2,4;a,e,k] | + | |
==Chapter 1: CT and DT Signals and Systems== | ==Chapter 1: CT and DT Signals and Systems== | ||
Revision as of 05:29, 8 December 2008
Contents
- 1 Summary of Information for the Final
- 1.1 ABET Outcomes
- 1.2 Chapter 1: CT and DT Signals and Systems
- 1.3 Chapter 2: Linear Time-Invariant Systems
- 1.4 Chapter 3: Fourier Series Representation of Period Signals
- 1.5 Chapter 4: CT Fourier Transform
- 1.6 Chapter 5: DT Fourier Transform
- 1.7 Chapter 7: Sampling
- 1.8 Chapter 8: Communication Systems
- 1.9 Chapter 9: Laplace Transformation
- 1.10 Chapter 10_ECE301Fall2008mboutin: z-Transformation
Summary of Information for the Final
ABET Outcomes
- (a) 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;a]
- (b) an ability to determine the impulse response of a differential or difference equation. [1,2;a]
- (c) an ability to determine the response of linear systems to any input signal convolution in the time domain. [1,2,4;a,e,k]
- (d) an understanding of the deffnitions and basic properties (e.g. time-shifts,modulation, Parseval's Theorem) of Fourier series, Fourier transforms, bi-lateral Laplace transforms, Z transforms, and discrete time Fourier trans-forms and an ability to compute the transforms and inverse transforms of basic examples using methods such as partial fraction expansions. [1,2;a]
- (e) 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. [1,2,4;a,e,k]
- (f) an ability to apply the Sampling theorem, reconstruction, aliasing, and Nyquist theorem to represent continuous-time signals in discrete time so that they can be processed by digital computers. [1,2,4;a,e,k]
