Dynamic Iterative Pursuit

  title={Dynamic Iterative Pursuit},
  author={D. Zachariah and S. Chatterjee and M. Jansson},
  journal={IEEE Transactions on Signal Processing},
  • D. Zachariah, S. Chatterjee, M. Jansson
  • Published 2012
  • Mathematics, Computer Science
  • IEEE Transactions on Signal Processing
  • For compressive sensing of dynamic sparse signals, we develop an iterative pursuit algorithm. A dynamic sparse signal process is characterized by varying sparsity patterns over time/space. For such signals, the developed algorithm is able to incorporate sequential predictions, thereby providing better compressive sensing recovery performance, but not at the cost of high complexity. Through experimental evaluations, we observe that the new algorithm exhibits a graceful degradation at… CONTINUE READING

    Figures and Topics from this paper.

    Distributed predictive subspace pursuit
    • 10
    Variational Bayesian dynamic compressive sensing
    • 10
    • PDF
    Distributed greedy pursuit algorithms
    • 41
    • PDF
    Dynamic Filtering of Time-Varying Sparse Signals via $\ell _1$ Minimization
    • 27
    • PDF
    Methods for Distributed Compressed Sensing
    • 13
    • PDF
    Online convex optimization meets sparsity
    • 1
    • PDF
    Re-Weighted l_1 Dynamic Filtering for Time-Varying Sparse Signal Estimation
    • 10
    • PDF
    Greedy Algorithms for Distributed Compressed Sensing
    • 4
    • PDF


    Publications referenced by this paper.
    Subspace Pursuit for Compressive Sensing Signal Reconstruction
    • 1,900
    • PDF
    Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
    • 7,242
    • PDF
    Uniform Uncertainty Principle and Signal Recovery via Regularized Orthogonal Matching Pursuit
    • 868
    • PDF
    Look ahead orthogonal matching pursuit
    • 39
    • PDF
    Kalman filtered Compressed Sensing
    • 289
    • PDF
    CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
    • 1,095
    • PDF
    Sparse signal recovery in the presence of correlated multiple measurement vectors
    • 49
    • PDF
    An Introduction To Compressive Sampling
    • 7,840
    • Highly Influential
    • PDF
    Stable signal recovery from incomplete and inaccurate measurements
    • 6,207
    • PDF