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Graduate Course Proposal Form Submission Detail - EEL6722C
Tracking Number - 3083

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Current Status: Approved by SCNS - 2016-01-26
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments: to GC 5/6/13. Elective (subm as 6935; updated to 6722). Obj need revision. Faculty emailed 5/10/13. Reviewed. still need rev. faculty emld 8/5/13. uptd 10/11/13. Still need rev. Emld 10/28/13. GC appd; to USF Sys 12/10; to SNCS 12/18. Apprd Eff 9-1-15

Detail Information

  1. Date & Time Submitted: 2013-02-11
  2. Department: Electrical Engineering
  3. College: EN
  4. Budget Account Number: 210600
  5. Contact Person: Ravi Sankar
  6. Phone: 8139744769
  7. Email:
  8. Prefix: EEL
  9. Number: 6722C
  10. Full Title: DSP/FPGA Laboratory
  11. Credit Hours: 3
  12. Section Type: L - Laboratory
  13. Is the course title variable?: N
  14. Is a permit required for registration?: N
  15. Are the credit hours variable?: N
  16. Is this course repeatable?:
  17. If repeatable, how many times?: 0
  18. Abbreviated Title (30 characters maximum): DSP/FPGA Lab
  19. Course Online?: C - Face-to-face (0% online)
  20. Percentage Online: 0
  21. Grading Option: R - Regular
  22. Prerequisites:
  23. Corequisites: EEL 6502 – Digital Signal Processing I
  24. Course Description: Development of real-time digital signal processing (DSP) systems from algorithm to hardware using DSP, FPGA and hybrid DSP/FPGA rapid prototyping platforms. The course has both lecture and laboratory components.

  25. Please briefly explain why it is necessary and/or desirable to add this course: Replacing Selected Topics with Permanent number; already listed in program
  26. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? Approximately 10-20 students enroll each Fall for this course.
  27. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? Yes, 3 or more times
  28. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) Familiarity with real-time DSP systems, DSP hardware, software, and embedded systems
  29. Objectives: 1. Learn the process of developing digital signal processing (DSP) systems from algorithms to real-time implementations

    2. Implement DSP algorithms using hardware DSP platforms and software such as MATLAB/Simulink, Code Composer Studio, and Real-Time Workshop

    3. Learn fundamental theory, design of algorithms, and implementation through several structured laboratory experiments on sampling, analog-to-digital conversion, digital filtering, spectral analysis, modulation, source/channel coding, adaptive noise and echo cancellation

    4. Introduce the connection between theory and applications, to algorithm design and hardware implementation of DSP for practical application

    5. Experiment using FPGA and hybrid DSP/FPGA platforms and explore advanced signal processing projects in the areas of signal processing and digital wireless communications

  30. Learning Outcomes: At completion of this course, students should be able to: 1) use various software tools such as Matlab, Simulink, Code Composure Studio for the development of DSP algorithms; 2) use various hardware platforms such as DSP, FPGA, hybrid and evaluate which platform is best suited for specific application; 3) carry out design of software algorithm to hardware implementation of various communications and signal processing topics including sampling, analog-to-digital conversion, digital filtering, modulation, coding, adaptive noise and echo cancellation, wireless communications, speech processing.
  31. Major Topics: 1. Fundamental Theory:

    Introduction to DSP architectures and programming

    Sampling Theory, Analog-to-Digital Converter (ADC), Digital-to-Analog Converter (DAC) and Quantization; Decimation, Interpolation, Convolution, Simple Moving Average; FIR and IIR Filters; Fourier Transform (DFT/FFT), Windows and Spectral Analysis; Digital Communication System: Source Coding, Channel Coding, Modulation, Matched Filter/Correlator, Equalizer;

    2. Design (Simulation) using MATLAB/ Simulink and C

    Simulate the lab exercises using MATLAB/Simulink Blockset and/or using C programming; Implementation using different DSP, FPGA and hybrid DSP/FPGA platforms; Digital Communications: On-Off- Keying (OOK), BPSK modulation, and a simple transceiver design; Adaptive Filtering: Echo/Noise Cancellation, Least Measure Square(LMS)algorithm; Wireless Communications: Equalization, Simple Detection Algorithm, OFDM Speech Processing: Linear and Cepstral Prediction Algorithms, Speech Classification and Synthesis

  32. Textbooks: DSP/FPGA Laboratory Manual, J. Norstrom and R. Sankar, University of South Florida, 2005-2012.

    DSP/FPGA Laboratory Course Handouts, R. Sankar, USF.

  33. Course Readings, Online Resources, and Other Purchases: Blackboard readings assigned (see syllabus)
  34. Student Expectations/Requirements and Grading Policy: Assessment is based on pre-lab assignments and post-lab reports for basic and advanced exercises, final project (report and oral poster presentation), and exam.
  35. Assignments, Exams and Tests: Grades will be decided based on

    Basic Lab Exercises (4) – 40 %

    Advanced Lab Exercises (2) – 30 %

    Project (1) – 30 %

  36. Attendance Policy: Course Attendance at First Class Meeting – Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation – Registration - 4.0101,

    Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (

    In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. It’s the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.

  37. Policy on Make-up Work: Academic Dishonesty Policy: Students are reminded that University policies pertaining to academic dishonesty commonly found in both UG and G catalogs will be applied in this course. Any form of cheating on exams or plagiarism on assigned homework and projects will result in an FF grade and further suspension or expulsion from the University with NO warnings given. Receiving or providing help on exams, assignments and project; Sharing of program codes and results, and not turning in individual work are all forms of cheating; Submissions that are "identical" in any way are clear evidence of cheating. Copying materials from textbooks and papers without properly referencing them or not giving due credit are forms of plagiarism. It is the student's responsibility to review and understand USF and EE Department policies and procedures on Academic Conduct, Dishonesty, and Disruption.
  38. Program This Course Supports: Electrical Engineering Masters and Doctoral programs
  39. Course Concurrence Information: Any engineering student needing the knowledge of real-time implementation of algorithms and system prototyping will benefit from the course

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