Now showing items 1-6 of 6

    • Collaborative Compressive Spectrum Sensing in a UAV Environment 

      Chen, Kevin; Kung, H. T.; Vlah, Dario; Hague, Daniel; Muccio, Michael; Poland, Brendon (Institute of Electrical and Electronics Engineers, 2011)
      Spectrum sensing is of fundamental importance to many wireless applications including cognitive radio channel assignment and radiolocation. However, conventional spectrum sensing can be prohibitively expensive in computation ...
    • Compressed Statistical Testing and Application to Radar 

      Chen, Hsieh-Chung; Kung, H. T.; Wicks, Michael C. (2012-12-06)
      We present compressed statistical testing (CST) with an illustrative application to radar target detection. We characterize an optimality condition for a compressed domain test to yield the same result as the corresponding ...
    • Gradient Descent for Optimization Problems With Sparse Solutions 

      Chen, Hsieh-Chung (2016-05-18)
      Sparse modeling is central to many machine learning and signal processing algorithms, because finding a parsimonious model often implicitly removes noise and reveals structure in data. They appear in applications such as ...
    • Measurement Combining and Progressive Reconstruction in Compressive Sensing 

      Chen, Kevin; Kung, H. T.; Vlah, Dario; Suter, Bruce (Institute of Electrical and Electronics Engineers, 2011)
      Compressive sensing has emerged as an important new technique in signal acquisition due to the surprising property that a sparse signal can be captured from measurements obtained at a sub-Nyquist rate. The decoding cost ...
    • Separation-Based Joint Decoding in Compressive Sensing 

      Chen, Kevin; Kung, H. T. (Institute of Electrical and Electronics Engineers, 2011)
      We introduce a joint decoding method for compressive sensing that can simultaneously exploit sparsity of individual components of a composite signal. Our method can significantly reduce the total number of variables decoded ...
    • Wireless Inference-based Notification (WIN) without Packet Decoding 

      Chen, Hsieh-Chung; Kung, H. T. (USENIX Association, 2013)
      We consider ultra-energy-efficient wireless transmission of notifications in sensor networks. We argue that the usual practice where a receiver decodes packets sent by a remote node to acquire its state or message is ...