This is supplemental course information, designed to give you a fuller picture of the course and an expanded look at the topics covered. This is an unofficial document. The USC Course Catalog is the binding description of all university courses. Information such as books, materials covered, and the order of topics is subject to change. Please consult instructor for this semseter to get more upto date course information.
Catalog Data:
434L Digital Signal Processing Design Laboratory (4, Fa): Experiments and design project in digital signal processing (e.g., real-time DSP, acoustics, video) including: systems specification, preliminary analysis, trade-off studies, implementation, presentation. Prerequisite: EE 483 and departmental approval.
Text book:
DSP Applications Using C and the TMS320C6x DSK, Rulph Chassaing, John Wiley & Sons, 2002.
Course Coordinators:
Richard M. Leahy, Professor of Electrical Engineering
Topics:
1. Introductory experiments to familiarize students with the practical implications and applications of digital signal processing theory in a real-time environment (including studies of sampling, aliasing, spectral analysis, digital filtering, and system identification).
2. Learning the architecture and assembler programming of a real-time DSP processor.
3. Apply knowledge of assembler programming to implement real-time fixed-coefficient FIR and IIR filters and adaptive noise-cancellation filters.
4. Work in teams of 2 or 3 to design, implement and test a real-time DSP system for a real world application (topics have included: active noise control, biomedical signal analysis, acoustic beamforming arrays for direction finding, automated speaker identification, and digital watermarking).
5. Preparation of project proposals, progress reports and final reports and oral presentation of progress and final reports with demonstration of a working system.
Course Objectives:
To provide a capstone design experience in which students apply knowledge acquired in their earlier coursework (and particularly digital signal processing, microprocessor architecture and assembler programming) to solve a real-world design problem.
Course Outcomes:
The students will be able to:
1. Explain and demonstrate on a real-time DSP system the practical implications of the sampling theorem on sampling and reconstruction of analog signals.
2. Explain and demonstrate the principles of Fourier-based spectral analysis with an understanding of the practical implications of window selection, zero-padding and sample frequency.
3. Describe the specific architecture of the DSP processor used in this class, and understand the architecture of similar commercially produced DSP processors.
4. Write assembler code to implement basic DSP algorithms such as linear filtering with FIR and IIR filters and adaptive IIR filters for noise cancellation.
5. Complete an open-ended design project with an improved understanding of practical issues of time management and the need for task sharing between members of the design team.
6. Prepare and present a technical report on all aspects of the design process: system specification, simulation/theoretical evaluation for system design and cost/performance trade-off studies, implementation and code debugging.
7. Better understand the relationship between the academic course work taken at the B.S. level and the problems that might be encountered in a research or commercial environment.
Laboratory Projects:
Brief reports are required for the preliminary experimental studies of basic principles of real time DSP. For the open-ended design projects, each time is required to submit a system design proposal, progress report and final report.
Prepared by: Richard M. Leahy Date: Sept 30, 2002
