Digital Signal Processing
This course provides an introduction to digital signal processing (DSP),
with equal emphasis on theory and applications.
Hands-on experience with DSP
will be obtained through computer projects in
Matlab and real-time processing with the dSPACE hardware units.
The course topics include discrete transforms,
the fast Fourier transform (FFT) algorithm, applications of the FFT
for spectral analysis, the Z-transform,
algorithms and applications of correlation and convolution,
and adaptive signal processing.
Laboratory projects will be chosen from application areas that include
digital audio processing, communication systems, signal analysis,
and acoustic echo processing for object location (similar to sonar
Students will also design and implement a DSP project for a particular
application area that is chosen by the student.
Instructor and Office Hours:
Richard J. Kozick
Office: Room 220 Dana
Phone: (717) 524-1129
FAX: (717) 524-1822
Tentative office hour schedule is as follows:
(Refer to the
course home page for the most up-to-date schedule)
M 10:00-11:00 AM
W 1:00-2:00 PM
R 11:00 AM - 12:00 Noon
F 2:00-3:00 PM
Other times by appointment -- please send me
email to arrange.
EE 205 or undergraduate course in signals and linear systems.
Emmanuel C. Ifeachor and Barrie W. Jervis,
Digital Signal Processing: A Practical Approach,
Course Home Page:
Follow the link from
or go directly to
The course home page contains the homework assignments,
links to other DSP pages,
and other course information.
The grading in this course will be objective, so that
you are not competing against one another for a limited number of
high grades. There is no ``curve'' that prescribes the number of
A's, B's, C's, etc. - it is possible for the entire class to earn A's.
The intent of this policy is to encourage cooperation among the class.
I hope everyone does well, and I hope we can all work together
to grow in our understanding of digital signal processing.
2 Quizzes at 15% each 30%
Final exam 20%
Lab projects 20%
Independent project 20%
The dates for the quizzes are listed on the tentative outline below.
Homework will be assigned regularly.
It will be due at the beginning of class on the specified due date.
Late assignments will be accepted but will be
reduced in grade.
You are encouraged to work on the homework with groups of your classmates.
The purpose of the homework is to practice with the material and to
improve your understanding.
I encourage you to learn from each other, and also ask me when you have
However, the homework solutions that you submit for grading
must be written individually .
Be sure that you understand the reasoning for each problem,
even if you initially solved the problem with help from your
Keep in mind that most of your grade in this course is determined by
exams and quizzes, which you will have to do by yourself.
Each student will complete an independent project on a topic
of the student's choice.
Proposals for the project are due on Friday, March 14, 1997.
Students will present their projects to the class during the
last week of the semester.
Some possible project topics are listed below.
Listed below is a tentative schedule of the course topics and lab projects.
- Week 1: (Chapter 1)
Introduction to DSP and its applications.
Basic DSP operations and system components (sampling,
A/D and D/A conversion).
Experiment with basic real-time DSP systems that include
analog-to-digital converters (ADC), digital-to-analog converters (DAC),
and digital filters.
Illustrate the sampling theorem.
- Weeks 2-4: (Chapter 2)
Discrete transforms -- definition, interpretation, and applications.
Particular transforms: discrete Fourier transform (DFT) and
discrete cosine transform (DCT).
Understand the FFT algorithm that efficiently computes the DFT.
Apply the FFT to analyze the frequency (or spectral)
content of various data sets.
Write a computer program to implement an FFT algorithm.
- Weeks 5-6: (Chapter 3)
The Z-transform: forward and inverse, system transfer function, applications
to frequency response and digital filter design by pole-zero placement.
Digital filter realization structures,
digital waveform generators, digital audio effects
(delays, echoes, flanging, chorusing, reverberation, etc.),
noise reduction filters.
Quiz 1: Friday, February 28, 1997.
- Weeks 7-8: (Chapter 4)
Correlation and convolution: applications and efficient
algorithms for computation.
Matched filters for digital communication in noise,
DSP for acoustic echo location using weak signals in noise.
Project Proposals Due: Friday, March 14, 1997.
Spring Recess: Begins Friday, March 14 at 5 PM and
ends Monday, March 24 at 8 AM.
- Weeks 9-11: (Chapters 5-7)
Digital filter design: fundamental ideas, FIR and IIR filters,
quantization effects, real-time implementation and applications.
Write a C program to implement a digital filter, and run the filter
in real-time on DSP chip.
Experiment with various filter types to process real signals.
Quiz 2: Friday, April 11, 1997.
- Weeks 12-14: (Chapter 9)
Adaptive signal processing: Wiener filter, LMS algorithm,
Adaptive digital filters for communication channel equalization
and other applications.
- Week 15:
Presentation of student projects.
Possible Topics for Projects:
Some possible topics for the project are listed below.
You are free to choose other topics not on this list.
For project ideas, you might consult library books on DSP as
well as the
Web links I have assembled.
Feel free to discuss project ideas with me at any time.
- Spectral analysis: classical (FFT) and modern (model-based)
- DSP for communication systems (modulation, equalization, CDMA)
- Signal compression (speech, audio, image, video)
- Digital image processing (most DSP topics are applicable to images also)
- Wavelet transform: what it is, and applications in DSP
- Adaptive signal processing (many fascinating applications)
- Digital audio processing (special effects, computer music)
- Digital synthesis of musical instruments
- Touch-tone (DTMF) generation and detection for telephone
- Digital control systems
- Modern digital filter design methods (based on optimization theory)
- Quantization in digital filters, power-of-two design methods
- FFT algorithms (many different types of algorithms exist)
- Digital speech processing
- Multirate signal processing and filter banks
- Electrocardiogram and other medical signal processing applications
- Adaptive equalizers and echo cancelers for modems
- Neural networks
- Modeling and prediction of random signals (try to predict the stock market!)
- Parallel, recursive filter architectures for computation of
- Deconvolution applications
- Analog-to-digital and digital-to-analog conversion methods
- Hardware architectures for DSP