The class covers necessary concepts of Digital Signal Processing and gives the student the opportunity to apply them on DSP technology and visualize these concepts using computer graphic techniques. Coverage will include Discrete-Time Signals, Z-transforms, discrete-time system modeling, digital filter design, Discrete Fourier Transform, Fast Fourier Transform, sampling theory and DSP implementation. Special emphasis will be given to emulating discrete-time systems using numerical methods. For example, a DSP operates on discrete-time sequences which are converted to and from continuous time. To model a continuous time system with a computer model, it must be approximated with discrete time samples. Thus, a computer model of a DSP has two levels of sampling, one for the DSP sequences and the other for the continuous time waveforms. This paradigm is relevant to many real world problems. Material will be drawn from chapters 1 through 9 of the text with emphasis on practical application. We expect that this course will help graduate students by giving them the discrete-time theory and experience allowing them to conduct their research and development, beyond just the class room.

As part of the homework assignments, the students will implement a series of tasks using MATLAB. These tasks will typically yield graphical outputs allowing the students to visualize the underlying concepts. Most tasks will be accumulative in nature although some will be used to clarify concepts found difficult to understand. One series of tasks will demonstrate how sampling can be used to obtain high resolution imagery by way of "synthetic aperture" imaging techniques. The concepts of synthetic aperture, point spread function deconvolution and subpixel sampling will be clarified for the student through this sequence of visualization tasks. Other tasks may involve FFT, discrete time filtering, and Z transform concepts.

The projects will involve implementing typical DSP functions on special hardware, measuring performance and writing lab reports. Projects are designed to step the student through the usage of the TMS320c50 processor while allowing hands on experience with DSP theory.

• Homework: 30%: Once a week, Due one week after assignment, No late homework, drop the lowest 1. At most, one visualization task per homework.
• Lab Projects: 30%: 5 projects, teams will be limited to 2 people per team.
• Exam 1: 20% (Date to be announced, closed book, 1 page crib sheet).
• Exam 2: 20% (Date to be announced, take home exam, MATLAB task).

1. Discrete-Time Signal Processing by A.V. Oppenheim and R.W. Schafer, Prentice Hall.
2. Digital and Analog Communication Systems by Leon W. Couch, Fourth Edition.
3. Principles of Communications, Systems, Modulation, and Noise by R, E. Ziemer and W. H. Tranter, Third Edition.
4. Introduction to Fourier Optics by J. W. Goodman, McGraw Hill.
5. Digital Communication by E. A. Lee and D. G. Messerschmitt.
6. Digital Transmission of Information by R. E. Blahut.
7. Introductory Probability and Statistical Applications by P. L. Meyer.
8. Probability and Statistics by M. H. DeGroot.
9. Digital Communication Systems by Simon Haykin.
10. An Introduction to Analog & Digital Communications by Simon Haykin.
11. Communication Systems by Simon Haykin, Second Edition.