KF-CS: Compressive Sensing on Kalman Filtered Residual

  title={KF-CS: Compressive Sensing on Kalman Filtered Residual},
  author={Namrata Vaswani},
We consider the problem of recursively reconstructing time sequences of sparse signals (with unknown and time-varyingsparsity patterns) from a limited number of linear incoherent measurements with additive noise. The idea of our proposed solution, KF CS-resi dual (KFCS) is to replace compressed sensing (CS) on the observation by CS on the Kalman filtered (KF) observation residual computed using the previous estimate of the support. KF-CS error stability over time is studied. Simulation… CONTINUE READING


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Compressive sensing on the least s quares and kalman filtering residual for real-time dynamic mri and video reconstruction,”IEEE

  • C. Qiu, N. Vaswani
  • 2009
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