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Signal and Image Processing

 

Program encompasses issues related to the modeling of signals, starting from the relevant physics, developing and evaluating algorithms for extracting information from the signal, and implementing these algorithms in both software and hardware. Theoretical areas include:

  • Transform theory
  • Statistical signal processing
  • Linear systems theory
  • Sensor array processing
  • Pattern recognition
  • Machine Learning

Application areas:

  • Sonar
  • Radar
  • Speech compression and recognition
  • Image compression, analysis & processing
  • Video compression, analysis & processing
  • 3D video compression, processing and visualization
  • Computer audition, Music information retrieval
  • Multimedia
  • Computer vision
  • Sensor networks
  • Wireless communications

 

 

Faculty: Pamela Cosman • Kenneth Kreutz-Delgado • Gert Lanckriet • Truong Nguyen • Alon Orlitsky • Bhaskar Rao • Mohan Trivedi • Nuno Vasconcelos • Kenneth Zeger • William Hodgkiss • James Zeidler