Course Description:
The course covers theory and methods for digital signal processing
including basic principles governing the analysis and design of
discretetime systems as signal processing devices. Review of
discretetime linear, timeinvariant systems, Fourier transforms
and ztransforms. Topics include sampling, impulse response,
frequency response, finite and infinite impulse response systems,
linear phase systems, digital filter design and implementation,
discretetime Fourier transforms, discrete Fourier transform, and
the fast Fourier transform algorithms.
Repeatability:: This course may not be repeated for additional
credits.
Prerequisites:: ECE 3522  Minimum Grade of D 
May not be taken concurrently.
Course Overview:
The field of Digital Signal Processing (DSP) continues to evolve
and play a central role in modern electronics. In fact, DSP is so
ubiquitous that the field is somewhat disappearing as a discrete
entity. Many systems today, such as IMAX, HDTV, mp3 players,
Internet audio and video, and Voice over IP, use powerful DSP
concepts as their foundations. DSP is a logical extension of
Signals and Systems in which we take a comprehensive view of
discretetime systems. The course covers the essential elements of
a DSP system from A/D conversion through powerful statistical
modeling algorithms. This course includes both theory and practice
with an emphasis on how to implement efficient algorithms in
C/C++. We begin with a discussion of basic DSP concepts such as
sampling and discretetime signal representations. We the discuss
traditional topics such as transforms and filter design. We
conclude with a discussion of implementation issues. An integral
part of the course are computer assignments designed to reinforce
theoretical concepts. MATLAB is is used as well to rapidly
prototype algorithms. C/C++ is used to understand how to
efficiently implement algorithms.
Course Learning Objectives (CLO):

Identify the signals and systems (SO A)

Apply the principles of discretetime signal analysis to perform
various signal operations (SO A, E)

Apply the principles of ztransforms to finite difference
equations. (SO A, E)

Apply the principles of Fourier transform analysis to
describe the frequency characteristics of discretetime signals
and systems (SO A, E)

Apply the principles of signal analysis to filtering (SO A, C, E)

Use computer programming tools to process and visualize signals (SO K)
Student Outcomes (SO):
 SO A: Ability to apply current knowledge and applications
of mathematics, science, engineering and technology
 SO C: Ability to creatively design a system, component
or process to meet desired needs within realistic constraints
such as economic, environmental, social, political, ethical, health
and safety, manufacturability, and sustainability
 SO E: Ability to identify, formulate, analyze and
solve technical and engineering problems
 SO K: Ability to use the techniques, skills and modern
technical tools necessary for technical or engineering practice
Course Topics: Refer to the SOs above to understand how these
topics relate to our stated student outcomes.

Classification of discretetime signals and systems,
convolution (CLO 1, 2)

Discretetime Fourier transform (CLO 4)

LTI systems, Impulse response and frequency response (CLO 2)

Finite difference equations, and z transforms. (CLO 3)

Sampling of continuoustime signals.(CLO 2,4,5)

Digital filter structures, block diagrams, signal flowgraphs, and
basic FIR digital filter structures (CLO 2, 4, 5)

Ideal filters, FIR and IIR filters, filter design (CLO 2, 4, 5)

Discrete Fourier transform (CLO 4)
Questions or comments about the material presented here can be
directed to