©CSU, Chico Electrical and Computer Engineering Department- ECE 141

CSU, Chico Department of Electrical and Computer Engineering

EECE 365:Continuous-Time Signals and Transforms

Prerequisites:EECE 311,MATH 260

Required for EE and CMPE majors

Catalog Description:Theory and application of Fourier series, Fourier transforms, and Laplace transforms. Parseval's Theorem, convolution and transfer functions. System modeling and simulation. topics from linear algebra, and introduction to partial differential equations. Formerly ECE 141.

Course Objectives:

teach the use of periodic signals and Fourier series to analyze circuits
explain the general linear system theory for continuous-time signals and systems using convolution
explain the general linear system theory for continuous-time signals and systems using the Fourier Transform
explain the general linear system theory for continuous-time signals and systems using the Laplace transform
explain the nature and occurrence of difference equations and discrete-time signals
explain how to analyze discrete-time systems using convolution and the z-transform
explain the effect of sampling on the frequency response of a signal
teach the Fast Fourier Transform (FFT) algorithm and its relationship to other transforms

Goals : For ECE juniors to develop skills of modeling and analyzing Signals and Dynamic Systems, continuous and digital, in both time and frequency domains, and for use in system control.

TOPICS : 1. Signal representation.

2. System classification.

3. Singularity functions.

4. Convolution.

5. The Laplace Transform

6. System Modeling, Transfer Functions and Stability.

7. System Frequency Response and Introduction to Ideal filters.

8. State Space modeling of linear continuous-time systems.

9. State Space analysis of linear continuous-time systems.

10. Discrete-time systems and the Z-transform.

11. Introduction to state variable analysis of linear discrete-time systems.

12. Fourier transforms.

13. Fourier analysis of discrete systems: An introduction.

14. Fourier series and its applications.

15. Computer simulation using MATLAB.

Course Outcomes: Students shall be able to:

recognize a periodic function and to calculate its trigonometric and complex Fourier series
analyze circuits with periodic sources using the Fourier series
calculate the output of a linear system using convolution and the Fourier transform
find the frequency content and signal energy using the Fourier transform
calculate the Laplace transform and its inverse
apply the Laplace transform to linear system modeling, transfer function, and stability
recognize the nature of discrete-time signals and their occurrence in engineering
calculate the z-transform of a discrete-time signal and understand its properties
calculate the impulse response, convolution, transfer function and stability for continuous and discrete systems
Model, analyze, and test stability of linear systems in the state space
find the output of a discrete-time linear system and to solve linear difference equations
calculate the discrete-time Fourier transform and use it to find the frequency response of a simple digital filter
identify the relationship between the various discrete-time transforms and the Fourier transform of the original continuous-time signal before sampling

Class/Laboratory schedule:

One hundred and fifty minutes a week lecture

Contribution of Course to Meet the Professional Component:

Engineering Science: 3 units

Relationship of Course to Program Outcomes and Objective:

This course makes significant contributions the following program outcomes:

An ability to apply knowledge of math, science and engineering
An ability to identify, formulate and solve engineering problems

This course supports the achievement of the following elements of the program objective:

Apply knowledge of mathematics, science, and engineering to identify, formulate, and solve computer engineering problems
Achieve success in graduate programs in computer engineering, electrical engineering or computer science.
Continue to develop their knowledge and skills after graduation in order to succeed personally and contribute to employer success.

ABET Embedded Assessment Components for this course:

Metric: The measure of student proficiency (e.g., a quantitative or qualitative measure of achievement on an assignment or test question which emphasizes the target outcome)

Rubric: Evaluative conclusions versus corresponding descriptions of achievement level (e.g., highest score represents mastery)

Standard: Evaluative result that represents minimally acceptable achievement of proficiency

The following table describes the course embedded assessment components for this course.

Outcome k: An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice

Course

Description

Metric

Rubric

Standard

EECE 365

Matlab programming and simulations relating to the topics studied in the course EECE 365 Continuous Time Signals and Transforms namely signals, convolution of signals, spectrum of signals, Transform of signals and system response to signals.

Assessment will be based on an evaluation of 6 designated class assignments that require demonstration of proficiency in programming with MATLAB by writing codes to plot signals, evaluate convolution of signals and plot it, evaluate spectrum of signals and plot it, evaluate transforms of signals, plot time domain and frequency domain response of system. Each assignment is evaluated on a scale of 2 points.

A student will demonstrate successful completion of this outcome by adequately completing all 6 assignments with a total score of 8 out of the 12.

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