Graduate Studies Reports Access

Graduate Course Proposal Form Submission Detail - EEL6753
Tracking Number - 2699

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Current Status: Approved, Permanent Archive - 2012-01-26
Campus:
Submission Type: Change
Course Change Information (for course changes only): Reinstate the course, effective Spring
Comments: To SCNS for reinstatement 1/19/12 (GC 1/23/12). Approved eff 10/2006


Detail Information

  1. Date & Time Submitted: 2011-12-14
  2. Department:
  3. College: EN
  4. Budget Account Number:
  5. Contact Person:
  6. Phone:
  7. Email:
  8. Prefix: EEL
  9. Number: 6753
  10. Full Title: Digital Signal Processing III
  11. Credit Hours:
  12. Section Type: -
  13. Is the course title variable?:
  14. Is a permit required for registration?:
  15. Are the credit hours variable?:
  16. Is this course repeatable?:
  17. If repeatable, how many times?: 0
  18. Abbreviated Title (30 characters maximum):
  19. Course Online?: -
  20. Percentage Online: 0
  21. Grading Option: -
  22. Prerequisites:
  23. Corequisites:
  24. Course Description:

  25. Please briefly explain why it is necessary and/or desirable to add this course:
  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?
  27. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times?
  28. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.)
  29. Objectives: To familiarize the students with the theory and practice of advanced topics in signal processing. The topics will range from Adaptive Filters, Multi-dimensional Signal Processing, Wavelets and Sub-band Analysis, to Signal Processing Applications. Each time the course is offered, a specific topic or topics will be focused for coverage.
  30. Learning Outcomes: 1. Students will learn the advanced signal processing techniques and algorithms applied in various topics in signal processing and its applications.

    2. Students will understand software tools and programs such as MATLAB to better understand the signal processing algorithms and for practical implementation in various applications

  31. Major Topics: Major Topics:

    Adaptive Filters

    1. Adaptive Systems

    2. Adaptive Linear Combiner

    3. LMS and other adaptive algorithms

    4. Adaptive Modeling and System Identification

    5. Adaptive Noise Canceling

    6. Adaptive Coding and Prediction

  32. Textbooks:
  33. Course Readings, Online Resources, and Other Purchases:
  34. Student Expectations/Requirements and Grading Policy:
  35. Assignments, Exams and Tests:
  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,

    http://usfweb2.usf.edu/usfgc/ogc%20web/currentreg.htm)

    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: (http://usfweb2.usf.edu/usfgc/gc_pp/acadaf/gc10-045.htm)

    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. Its 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:
  38. Program This Course Supports:
  39. Course Concurrence Information:


- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.