: Techniques in Signal and Data Processing
R. A. Pilgrim
Web Page URL
See Academic Web page: UserID: pilgrim, Password: access
Covers the numerical methods and algorithms used rto obtain iseful information from
ements. The performance characteristics of various types of signal generating and sensing devices and
the associated methods of signal conditioning, sampling, and analog
digital conversion are reviewed. Common
techniques in linear and non
ering, responsivitiy correction, data object detection, classification,
correlation, feature extraction, identification and state estimation are studied. Applications in speech recognition,
sound & image analysis, data compression, and telecommunications a
: The purpose of this course is to provide the student with a theoretical foundation in the principles
of signal and data processing and an understanding of their application to solving problems in real
1. Have a solid foundation in the mathematical and algorithmic methods in signal & data processing.
2. Understand the major issues in extracting signals from noisy measurements.
3. Understand the digit
ization process and its effects on the quality of signals.
4. Have experience with the various interface ports of desktop computers.
5. Be familiar with the frequency domain and its relationship to the time domain.
6. Underdanst the various image and sound file formats and how to access them in a program.
7. Have a practical knowledge of a library of signal and data processing functions.
Overview of Signal and Data Processing
Measurements and Noise
A Simple Example
Some Probability Distributions
Uniform, Binomial, Gaussian,
Generating Random Numbers
Methods in Data Reduction
1The Random Vector and Propagation of Errors
Time Domain Analysis
Basics of Time Varying Signals
Analog to Digital Conversion
Sampling and Aliasing
Decimation in Amplitude and Time
Types and Sources of Noise
A Virtual Signal Generator
Accessing WAV Files
Signal Detection and Adaptive Thresholds
Extracting Signals from Noisy Measurements
Convolution and Correlation
Frequency Domain Analysis
Building a Square Wave from Sine Waves
The Fourier Series
The Fourier Transform and Its Properties
The Fast Fourier Transform (FFT) Algorithm
Frequency Analysis and the Power Density Spectrum
Transform and Its Properties
The Effects of the Measurement System on a Measurement
Discrete Time Filtering IIR and FIR
High Pass, Low Pass and Band Pass Filters
Designing Discrete Time Filters
Accessing BMP Files
Feature Selection and Extraction
ds in Pattern Recognition
Image Segmentation and Partitioning
Overview of Data Processing
Building and Tracking Data Objects
Categorization of Data Objects
An Overview of Signal Processing Methods in Telecommuncations
Compression and Decompression in Voice Communicati
Speaker Identification and Voice Recognition
Compression and Decompression of Images
Spot Tracking and Scan
Automated Security and Surveillance
: Instructional activities include, lectures, instructor
directed laboratory exercises,
programming assignments, and 3 or 4 tests. In addition, lecture outlines, answers to selected homework problems,
sample programs and other cour
se related information are available on the Web.
Field and clinical Experiences
: Open and closed programming laboratories, compiler/IDE, Web page.
A 3/4 In
B Prog Assignments............. 20%
C Homework......................... 10%
D Presentation/Participation.. 20%
E Final Exam........................
Missing quiz grades will be made up during the
Final Exam. The Final Exam is required but
will be considered only if it improves your grade.
: The class role will be taken periodically. Students
are expected to attend class regularly.
Frequent absences could affect your homework/class participation grade. Late homework will not be graded for
: Permission of Instructor
Academic Honesty Policy
ating, plagiarism (submitting another person's work as your own), or doing
work for another person which will receive academic credit are all unacceptable forms of conduct and constitute
academic dishonesty. This includes the use of unauthorized books, no
tebooks or other sources in order to secure or
give help during an examination; the unauthorized copying of examinations, assignments, reports, computer files or
term papers; or the presentation of unacknowledged material as if it were your own work.
the policy of the
College of Business and Public Affairs that,
instances of academic dishonesty will receive appropriate
punitive action from the faculty member in whose class such dishonesty occurs
(2) the names of students
involved in acts of
academic dishonesty will be reported to the Dean.
Any student requiring additional
assistance due to a disability should inform the instructor as soon as possible.