Purdue University Calumet
School of Technology
Course Syllabus
ECET 39200 – Digital Signal Processing
Credits and Contact Hours:
Credit 3, Class 2, Lab. 3, Contact Hours 5
Instructor’s or Course Coordinator’s Name:
Essaid Bouktache
Text Book, Title, Author and Year:
Title: Fundamentals of Digital Signal processing.
Author: Joyce Van de Vegte.
Year: 2002.
Other supplemental material: Lab handouts and other handouts for topics not covered by the textbook.
Introduction to the Course:
a)Catalog Description (2010-2011 Academic Catalog):
Introduction to the fundamentals of digital signal processing: Discrete-time principles, sampling theorem, discrete Fourier transform , fast Fourier transforms, time and frequency domain considerations, Z-transform, solution of difference equations and design of digital filters.
b)Prerequisites:
ECET 38400 and ECET 20900 or Consent of Instructor.
c)Required course.
Specific Goals of the Course:
a)Course Learning Objectives:
Upon completion of this course, the student should be able to:
- Apply the fundamental principles of sampling and A/D conversion.
- Represent discrete-time signals in both time and frequency domain.
- Understand the various forms of number representation in DSP chips.
- Apply the following principles: Z-transform, Transfer Functions, Difference Equations, Impulse and Step Response, Digital Convolution.
- Compute and understand the importance of Frequency Response.
- Design and implement digital filters.
- Understand the basics of the Fast Fourier Transform (FFT) and its applications in spectral analysis.
- Acquire competency in using the MATLAB Signal Processing Toolbox.
- Gain hands-on experience with a DSP hardware platform for real-time implementation of DSP systems.
b)Criteria 3 Student Outcomes:
This course covers item a, b, and c in ABET Criteria 3.
Page 1 of 2
ECET 39200 - Digital Signal Processing
Course Delivery Methods (check all that apply):
X Lecture X Laboratory
Factors Used to Determine the Course Grade (check all that apply):
X Quizzes X Exams X Homework X Lab Reports
X How final grade is determined:
Each for exam 1 and 220%
Final exam25%
Quizzes 20%
Average of homework and lab reports15%
Brief List of Topics to be Covered:
1)Overview of Digital Signal Processing and its applications; basic DSP operations.
2)Sampled-data systems; data conversion devices: Sample-and-Hold (S/H), Analog-to-Digital (A/D) and Digital-to-Analog (D/A) devices; quantization;
3)The fundamental Sampling Theorem; spectrum of sampled signals; aliasing effects; recovery of an analog signal from its samples; effects of sampling in the frequency domain ;band-pass sampling.
4)Fixed and Floating Point Representations of Digital Signals.
5)Transfer function; unit impulse response; step response; stability of discrete systems.
6)The Discrete Time Fourier Transform (DTFT); Frequency response of discrete-time systems.
7)Digital Signal Spectra.
8)Realization of Digital Systems: Direct, cascade and parallel forms.
9)Digital Convolution.
10)Design of Finite-Impulse Response (FIR) digital filters.
11)Design of Infinite-Impulse Response (IIR) digital filters.
12)The Discrete Fourier Transform (DFT).
13)The Fast Fourier Transform (FFT): The Decimation-In-Time (DIT) algorithm; Inverse FFT; spectral analysis; Fast convolution.
Lab Experiments:
1)Frequency Spectrum of Sampled Sine Waves and Speech Signals.
2)Waveform Generation: An Introduction to the Texas Instruments TMS320C6713 DSK (Digital Signal Processor Kit).
3)A Talkthrough Program an Echo Program Using the TMS320C6713 DSK and Use of a Spectrum Analyzer.
4)Implementation of the Digital Integration Using the TMS320C6713 DSK
5)Digital Convolution: Theory and Implementation.
6)Frequency Response of Analog Filters.
7)Frequency Response of the TMS320C6713 DSK.
8)Frequency Response of Digital Systems.
9)Digital Signal Spectra.
10)Design and Implementation of FIR Digital Filters Using the Window Method.
11)Project 1: Design and Implementation of a Band-Stop FIR Digital Filter.
12)Project 2: Design and Implementation of a DTMF Tone Generator.
13)Spectrum Analysis Using the Fast Fourier Transform (FFT).
Page 2 of 2