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):

• Identify the signals and systems (SO A)
• Apply the principles of discrete-time signal analysis to perform various signal operations (SO A, E)
• Apply the principles of z-transforms to finite difference equations. (SO A, E)
• Apply the principles of Fourier transform analysis to describe the frequency characteristics of discrete-time 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 discrete-time signals and systems, convolution (CLO 1, 2)
• Discrete-time Fourier transform (CLO 4)
• LTI systems, Impulse response and frequency response (CLO 2)
• Finite difference equations, and z transforms. (CLO 3)
• Sampling of continuous-time signals.(CLO 2,4,5)
• Digital filter structures, block diagrams, signal flow-graphs, 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)