Difference between revisions of "EE 586L Advanced Digital Signal Processing Lab"

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'''EE 434L'''
'''EE 434L'''
* '''Lectures''' Monday, 3:30-4:30pm, B18
* '''Lectures''' Monday, 3:30-4:30pm, B18
* '''Lab hours''' M-4:30-5:30pm, W-4:00-5:30pm, F-3:30-5:00pm, B 18
* '''Lab hours''' M-4:30-5:30pm, W-4:00-5:00pm, F-10:00am-12:00pm, F-1:00-3:00pm, B 18
'''Teaching Assistants'''  
'''Teaching Assistants'''  
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** Email: smcphers AT usc DOT edu
** Email: smcphers AT usc DOT edu
** Tel: (213) 740-4655
** Tel: (213) 740-4655
** Office Hours: During Lab Hours
* Joohyun (Peter) Cho
** Email: joohyunc AT usc DOT edu
** Tel:
** Office Hours: During Lab Hours
** Office Hours: During Lab Hours

Revision as of 00:18, 26 January 2009

EE 586L and EE 434L, DSP Laboratory, Spring 2009

Course Description: Real-time signal processing experiments and design projects using special purpose DSP processor. Focus on C programming for embedded platforms. Understand real-time processing system issues including constraints of embedded systems and complexity analysis for improved algorithm design.

Prerequisites: EE 483, Introduction to Digital Signal Processing, or equivalent course and some course in C Programming. Please revisit material from both of these courses early on in the semester.

Recommended Preparation: EE 519, Speech Recognition and Processing for Multimedia, EE 522, Immersive Audio Signal Processing, EE 569, Introduction to Digital Image Processing, or EE 583, Adaptive Signal Proceesing. None of these courses are required.


Antonio Ortega

Signal and Image Processing Institute
Department of Electrical Engineering
University of Southern California
3740 McClintock Ave., EEB 436
Los Angeles, CA 90089-2564

Tel: (213) 740-2320
Fax: (213) 740-4651
Email: antonio DOT ortega AT sipi DOT usc DOT edu


EE 586L

  • Lectures Friday, 9-10:00pm, B 18
  • Lab hours Friday, 10:00-12:00pm and 1:00-3:00pm, B 18

EE 434L

  • Lectures Monday, 3:30-4:30pm, B18
  • Lab hours M-4:30-5:30pm, W-4:00-5:00pm, F-10:00am-12:00pm, F-1:00-3:00pm, B 18

Teaching Assistants

  • Sean McPherson
    • Email: smcphers AT usc DOT edu
    • Tel: (213) 740-4655
    • Office Hours: During Lab Hours
  • Joohyun (Peter) Cho
    • Email: joohyunc AT usc DOT edu
    • Tel:
    • Office Hours: During Lab Hours
  • Presentations
  • Final Demonstration Will be held on the last day of class


During the first few weeks assignments will be given out weekly to facilitate learning C programming for the DSP system. Mini projects may also be assigned periodically during the initial weeks. Grades will be determined based on completion of the assignments, mini projects, and the end of semester design project.

Blackboard Access

This semester I will use the Blackboard system to post assignments and solutions, as well as grades. Please register with Blackboard and create your Blackboard profile as soon as possible by following the instructions on the Blackboard Webpage Blackboard Website.



  • Rulph Chassaing, Donald Reay - Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK, 2nd Edition. Book Website


Material Covered (Subject to Change)

  • Week 1 Intro to boards and tools – Book Ch. 1-2
  • Week 2 Architecture – FIR-IIR Filters
  • Week 3 FFT – Adaptive Filtering
  • Week 4 Code optimization – Multirate Filtering
  • Week 5 Project discussion – Ideas and initial feedback
  • Week 6 Project proposals - Reviews
  • Weeks 5-13 Project
  • Week 10 Progress report + presentation
  • Week 14 Project demos/presentations – Final report


  • Project requirements:
    • Projects should be done in groups of 2-3.
    • Each project must perform some signal processing task in real-time using either the fixed or floating point DSP board. Common examples are adaptive, video or audio signal processing.
    • Project code should be optimized so that algorithms run efficiently on the DSP board.
    • The final demonstration of your project should clearly show the desired effect of your algorithm.
  • Reporting requirements: a final report and a class presentation.
    • Project guidelines will be posted on Blackboard

Sample Project Topics - Organized by Areas

  • Speech
    • Isolated Word Recognition
    • Speaker identification
    • Speech compression
      • LPC
      • ADPCM
  • Audio
    • Audio Compression
    • Active noise cancellation
    • Pitch to MIDI conversion
    • Speech/Music discrimination
    • 3D Audio
    • Blind acoustic source separation
  • Video
    • Video Compression
    • Video Tracking
    • Video Stitching
  • Communications
    • Baseband Modem