Publications of Cheng Cheng    :chronological  alphabetical  combined listing:

%% Papers Published   
@article{fds330512,
   Author = {Cheng, C and Jiang, Y and Sun, Q},
   Title = {Spatially distributed sampling and reconstruction},
   Journal = {Applied and Computational Harmonic Analysis},
   Volume = {47},
   Number = {1},
   Pages = {109-148},
   Publisher = {Elsevier BV},
   Year = {2019},
   Month = {July},
   url = {http://dx.doi.org/10.1016/j.acha.2017.07.007},
   Abstract = {© 2017 Elsevier Inc. A spatially distributed network
             contains a large amount of agents with limited sensing, data
             processing, and communication capabilities. Recent
             technological advances have opened up possibilities to
             deploy spatially distributed networks for signal sampling
             and reconstruction. In this paper, we introduce a graph
             structure for a distributed sampling and reconstruction
             system by coupling agents in a spatially distributed network
             with innovative positions of signals. A fundamental problem
             in sampling theory is the robustness of signal
             reconstruction in the presence of sampling noises. For a
             distributed sampling and reconstruction system, the
             robustness could be reduced to the stability of its sensing
             matrix. In this paper, we split a distributed sampling and
             reconstruction system into a family of overlapping smaller
             subsystems, and we show that the stability of the sensing
             matrix holds if and only if its quasi-restrictions to those
             subsystems have uniform stability. This new stability
             criterion could be pivotal for the design of a robust
             distributed sampling and reconstruction system against
             supplement, replacement and impairment of agents, as we only
             need to check the uniform stability of affected subsystems.
             In this paper, we also propose an exponentially convergent
             distributed algorithm for signal reconstruction, that
             provides a suboptimal approximation to the original signal
             in the presence of bounded sampling noises.},
   Doi = {10.1016/j.acha.2017.07.007},
   Key = {fds330512}
}

@article{fds330513,
   Author = {Li, L and Cheng, C and Han, D and Sun, Q and Shi, G},
   Title = {Phase Retrieval From Multiple-Window Short-Time Fourier
             Measurements},
   Journal = {Ieee Signal Processing Letters},
   Volume = {24},
   Number = {4},
   Pages = {372-376},
   Publisher = {Institute of Electrical and Electronics Engineers
             (IEEE)},
   Year = {2017},
   Month = {April},
   url = {http://dx.doi.org/10.1109/lsp.2017.2663668},
   Doi = {10.1109/lsp.2017.2663668},
   Key = {fds330513}
}

@article{fds330514,
   Author = {Cheng, C and Jiang, Y and Sun, Q},
   Title = {Sampling and Galerkin reconstruction in reproducing kernel
             spaces},
   Journal = {Applied and Computational Harmonic Analysis},
   Volume = {41},
   Number = {2},
   Pages = {638-659},
   Publisher = {Elsevier BV},
   Year = {2016},
   Month = {September},
   url = {http://dx.doi.org/10.1016/j.acha.2015.12.007},
   Doi = {10.1016/j.acha.2015.12.007},
   Key = {fds330514}
}

@article{fds330515,
   Author = {Chen, Y and Cheng, C and Sun, Q},
   Title = {Reconstruction of Sparse Wavelet Signals From Partial
             Fourier Measurements},
   Journal = {Ieee Signal Processing Letters},
   Volume = {22},
   Number = {12},
   Pages = {2299-2303},
   Publisher = {Institute of Electrical and Electronics Engineers
             (IEEE)},
   Year = {2015},
   Month = {December},
   url = {http://dx.doi.org/10.1109/lsp.2015.2478007},
   Doi = {10.1109/lsp.2015.2478007},
   Key = {fds330515}
}