FAIRFIELD UNIVERSITY
School of Engineering
Electrical Engineering Department

EE 356 – Discrete-Time Signals and Systems                    3 credits                     45 hours

Prerequisite:  EE 301 – Linear Systems (or equivalent)               

 

Description: This course serves as a bridge to understanding the relationship between the Analog world and its Discrete-Time representation in digital computers.  Digital Signal processing is covered with emphasis on the relationship between continuous-time and discrete-time systems in the time and frequency domains.  Practical aspects of digital filter design and implementation structures are discussed and the use of stochastic models to model quantization effects in digital signal processing is introduced.  Real world applications of Digital Signal Processing are analyzed to provide insight into the application of these techniques.  The design process of digital filers using computer tools is introduced in class.  Clarity in important DSP concepts is provided using MatLab and SystemView for exercises and experiments in digital signal processing techniques.

 

Student Outcome
Learning Goal

1.

Understanding of the relationship between discrete-time signals/systems and their real-world, analog counterparts.

Knowledge of Math, Science & Engineering

1.2

 

2.

Familiarity with the breadth of applications of DSP in today’s world.

Specialization and
Life Long Learning

0.4
0.2

3.

Ability to analyze and design digital filters to process discrete-time signals.

Problem Solving

0.4

Engineering Design

0.4

4.

Proficiency with MatLab and the Signal Processing Toolbox.

Use Modern Engineering tools

0.4

 

Text: “Introduction to Signal Processing,” Orfanidis, Prentice-Hall, 1996, ISBN 0‑13‑209172‑0

References:

1.     “Discrete-Time Signal Processing,” Alan V. Oppenheim and Ronald W. Schafer, Prentice-Hall, Second Edition, 1989

2.     “Digital Signal Processing: Principals, Algorithms, and Applications,”  John G. Proakis and Dimitis G. Manolakis, Macmillan, Second Edition, 1992

 

Software:

1.     MatLab, Simulink, Signal Processing Toolbox, DSP Blockset, Wavelet Toolbox
(Version 4.2c available from Instructor)

2.     SystemView, by Elanix (Student Edition) (available from Instructor)

 

Instructor:

Jeffrey N. Denenberg

Email:

jeffrey.denenberg@ieee.org.

Pre-Requisites:

EE 301 – Linear Systems (or equivalent)

Phone:

(203) 268-1021(days & eves.)

Textbook:

“Introduction to Signal Processing,” Orfanidis, Prentice-Hall,  1996, ISBN # 0‑13‑209172‑0

SW:

(Both available in class)

MatLab: Simulink, Signal Processing Toolbox, DSP Blockset, Wavelet Toolbox
SystemView:

Supplement:

Notes: http://doctord.webhop.net/

Exams:

Two (~5th&12th wk) - 30% ea.
Comprehensive final - 40%

Topics:

1.

Signals and Systems: Review

1.1 - 1.2, Notes

(0.5 weeks)

2.

Sampling of signals in the time and frequency domain

1.3 - 1.7, Notes

(1.5 weeks)

3.

Quantization

2.1 - 2.4

(1 week)

4.

Discrete-Time Systems

c3

(1 week)

 

Exam 1

 

 

5.

FIR filters and Convolution

c4

(1 week)

6.

The Z-Transform

c5

(1 week)

7.

Transfer Functions

c6

(1 week)

8.

Digital filter implementation structures

c7

(1 week)

 

Exam 2

 

 

9.

Efficient computation of the DFT: the FFT algorithms

c9

(1 week)

10.

FIR digital filter design

c10

(1 week)

11.

IIR digital filter design

11.1 - 11.4

(1 week)

12.

Topics in current digital signal processing applications
(Wavelet analysis, Sigma-Delta Modulator, Transmultiplexor, etc.)

c8, Notes
(not on Exams)

(1 week)

 

Final Exam

 

 

CLASS EXPECTATIONS

I. TEACHER

Distribute syllabus.

Review the material described in the syllabus.

Explain material.

Identify alternate reading assignments or books that clarify the material.

Relate material to "real world" situations when possible.

Answer questions.

Meet at a mutually convenient time to discuss problems.
          Telephone:                        (203) 268-1021
          Email:                               mailto:jeffrey.denenberg@ieee.org.

          Home Page:                      http://doctord.webhop.net/

          Class Office Hour:             5:30-6:30 PM, before class on Thursdays

Be receptive to new ideas.

Announce business/class conflicts in advance.

Make up missed classes.

Prepare and administer 3 exams.

Grade fairly.

Assign appropriate home problems.

Homework policy:

·       Reviewed in class

·       Collected or not collected

·       Graded or not

·       Quizzes

 

II. STUDENT

Review prerequisite material!!! (see web site for materials)

·       Differential Equations

·       Laplace Transforms

·       Transfer Functions

·       Convolution Integral

Ask questions.

Stay current.

Study the material described in the syllabus.

Complete the assigned homework.

Obtain class notes and homework if a class is missed.

Use the library to obtain supplemental material that explains an unclear topic.

Prepare for exams.

Ask for help! Before you fall behind.

 

MAKEUP CLASS DATES

An extra class will be held (probably on a Friday or Saturday) to introduce you to MatLab and SystemView.

Laboratory Experiences in Digital Signal Processing

Experiment

Purpose

Notes

Introduction to DSP

Underscore the effectiveness and breadth of real-world DSP applications

Speech Spectrograms, Speech Modeling, Speech Compression and
Active Noise Cancellation

Aliasing

Demonstrate the effects of aliasing on real signals

Aliasing shown visually in both time and frequency domains, audible effects are heard

Minimum Phase Filters

Derive equivalent minimum phase filters from linear phase prototypes

Introduces the importance of signal delay in filter designs

Quantization Noise

Relate classroom mathematics to the audible (and visual) effects of quantization.

Quantization is shown visually in both the time and frequency domains, audible effects are heard