EET-225 and EET-225L Devices I - John Sebeson
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Transcript EET-225 and EET-225L Devices I - John Sebeson
ECET-430
Advanced Digital Signal
Processing
4/8/2015
J. M. Sebeson
Important Information
Your professor: John Sebeson
Phone: (630)-652-8299
Email: [email protected] or
[email protected]
Web page: http://jsebeson.webs.com
This course does not use the eCollege shell
Office hours: see my faculty web page
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J. M. Sebeson
Course Resources Web
Page
Course syllabus
Assignment calendar
Lab Exercises
Homework coversheet
Other important information and files
4/8/2015
J. M. Sebeson
ECET-430
Advanced Digital Signal Processing
A sequel to ECET-350.
Covers techniques used in many current
applications of DSP.
Assumes concepts learned in ECET-350 (or EET350) and familiarity with MATLAB.
Lab involves MATLAB computational exercises
Some homework assignments require MATLAB.
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J. M. Sebeson
Text and other
requirements
J. Kronenburger and J. Sebeson, “Analog and
Digital Signal Processing: An Integrated
Computational Approach with MATLAB,”
Thompson Delmar Learning (Cengage
Learning), 2008. ISBN 1418041734
Scientific graphing calculator (TI-89
recommended)
MATLAB 7.0 or higher with Signal Processing
Toolbox (available on Citrix)
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J. M. Sebeson
Selected ECET-430 Topics
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4/8/2015
Review of key DSP concepts
Discrete Fourier analysis of sampled signals
Phase distortion and linear phase filters
Impulse response of ideal filters
Linear-phase FIR filter design
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Windowed ideal response
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Sampling method
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Optimal Parks-McClellan method
IIR filter design
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Digital oscillators
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Notch filters
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Analog prototypes by the bilinear transformation
Multi-rate techniques
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Digital anti-aliasing
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Decimation and interpolation
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Noise power density and sampling
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Noise-shaping, delta-sigma quantization
Correlation and auto-correlation of signals
Adaptive filters
Image processing
Wavelets
Case Studies
J. M. Sebeson
ECET-430 Lab
Lab consists of 8 MATLAB computational exercises
emulating the problems of a typical DSP engineer.
You are expected to complete the lab exercises on
your own initiative, just as a DSP engineer would.
Labs are not “cookbook.” You may need to study
lecture notes, textbook MATLAB user guides, and
MATLAB help documentation to complete them.
Late labs will not receive credit.
No labs are dropped.
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J. M. Sebeson
Grading Weights
Homework: 20%
Quizzes: 20%
Midterm Exam: 20%
Final Exam: 20%
Lab: 20%
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J. M. Sebeson
Grading Scale
Each element (and the total grade) is
based on a point system (rounded to the
nearest point) where:
90 to 100 = A (e.g. 89.51=90.0=A)
80 to 89.5 = B (e.g. 89.49 =89.0=B)
70 to 79.5 = C
60 to 69.5 = D
Below 60 = F
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J. M. Sebeson
Why Learn DSP With
MATLAB?
Digital Signal Processing is the dominant technology
today, and into the future, for small-signal electronic
systems (i.e., just about everything)
MATLAB has become one of the standard design
environments for DSP engineering
Technology students need to be literate and skilled in
this environment: knowledgeable in both DSP and
MATLAB
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J. M. Sebeson
MATLAB in DSP Product
Development
Develop and
Test Algorithms
in MATLAB
Code
Composer
SIMULINK
Simulation
DSP
Processor
Platform
MATLAB + PC = DSP Processor!! (just less efficient)
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J. M. Sebeson
My Background
Education:
B. S. Physics, 1969, Michigan State University
M. S. Electrical Engineering, 1971, Northwestern University
M. S. Materials Science and Engineering, 1973, Northwestern
University
Ph.D. Candidacy (ABT) Materials Science, 1978, Northwestern
University
Professional Experience: (1969 to Present)
2000 – Present: Professor, ECET, DeVry University
1989 - 2000: Hardware Development Director, Switching and Access
Solutions, Lucent Technologies
1985 - 1989: Head, Computer Engineering Information Department,
AT&T Data Systems Group
1979 - 1985: Technical Manager, Data Switching Product Engineering
Group, Bell Laboratories
1969 - 1979: Member of Technical Staff, Bell Laboratories
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J. M. Sebeson
Areas of R&D
4/8/2015
No. 5 Electronic Switching Systemtm
AT&T 3Btm Computers
No. 2 Signal Transfer Point
Common Channel Signaling (CCIS)
1A Processor (No. 1A ESStm and No. 4 ESStm )
Computer Aided Design
Signaling link encryption systems
Hybrid integrated circuit fabrication and testing
Magnetic bubble memory devices
Laser holographic mass memory systems
Reliability theory
Solid state surface physics
Molecular kinetics
J. M. Sebeson