RICE-UNIVERSITY

  标准压缩感知（CS）理论决定了可靠的信号恢复是可能给M= O（KLOG（N / K））的测量。我们证明了它可以通过利用超越简单的稀疏性和可压缩性由包括价值观和信号系数的位置之间的依赖关系更加逼真信号模型大大降低Mwithout牺牲的鲁棒性。(The standard compressive sensing (CS) theory dictates that robust signal recovery is  possible from  M=O(Klog(N/K))  measurements. We demonstrate that it is possible to substantially  decrease  Mwithout sacrificing robustness by leveraging more  realistic signal models that go beyond simple sparsity and  compressibility by including dependencies between values and  locations of the signal coefficients.   )