ECE 4522: Digital Signal Processing

Joseph Picone
Department of Electrical and Computer Engineering
Temple University

office: EA 703A
email: picone@temple
phone: 215-204-4841 (ofc), 662-312-4209 (cell)

Course Description: The course covers theory and methods for digital signal processing including basic principles governing the analysis and design of discrete-time systems as signal processing devices. Review of discrete-time linear, time-invariant systems, Fourier transforms and z-transforms. Topics include sampling, impulse response, frequency response, finite and infinite impulse response systems, linear phase systems, digital filter design and implementation, discrete-time 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 discrete-time 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 discrete-time 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): Student Outcomes (SO): Course Topics: Refer to the SOs above to understand how these topics relate to our stated student outcomes.
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