We study when a sub‐Gaussian matrix can become a near isometry on a set, show that previous best‐known dependence on the sub‐Gaussian norm was suboptimal, and present the optimal dependence. Our result not only answers a remaining question posed by Liaw, Mehrabian, Plan, and Vershynin ...
Random matrices have become a popular choice for the measurement matrix. Indeed, near-optimal uniform recovery results have been shown for such matrices. In this note we focus on nonuniform recovery using Gaussian random matrices and $\\\ell_1$-minimization. We provide a condition on the number...
This article characterizes uniform convergence rate for general classes of wavelet expansions of stationary Gaussian random processes. The convergence in p... Y Kozachenko,A Olenko,O Polosmak - 《Communications in Statistics》 被引量: 8发表: 2013年 On convergence of general wavelet decompositions of...
In this paper,sub-Gaussian random projection is introduced into compressed sensing(CS) theory and two new kinds of CS measurement matrix:sparse projection matrix and very sparse projection matrix are presented. 将亚高斯随机投影引入可压缩传感CS(compressed sensing)理论,给出了两种新类型的CS测量矩阵:稀...
{m imes m} is an m imes m m imes m matrix, and random vector X \\circ \\xi X \\circ \\xi denotes the Hadamard product of an isotropic subgaussian random vector X \\in \\mathbb{R}^m X \\in \\mathbb{R}^m and a random vector \\xi \\in \\{0, 1\\}^m \\xi \\in...
Gray level dependence matrix GLRLM: Gray level run-length texture matrix GLSZM: Gray level size zone matrix IBSI: Image Biomarker Standardization Initiative LRFS: Local recurrence-free survival LoG: Laplacian-of-Gaussian NGTDM: Neighborhood gray tone difference matrix ...
After transmission,wkis corrupted by the channel and noise, becomingrk. Equation (2) shows the correlation process, expressed (in its raw mathematical form) as the inner product of the received symbol,rkand the complex conjugate of symboli,wi∗. In the presence of Additive White Gaussian Nois...
As in quantum field theory, there are sources, excitations, fields, and the random background. Gaussian integration over the stochastic fields reveals the residual interactions between excitations. These are all describable by symmetry (Lie groups) with a gauge connexion. Generally speaking, all ...
MPSImageCopyToMatrix MPSImageDescriptor MPSImageDilate MPSImageDivide MPSImageEdgeMode MPSImageErode MPSImageEuclideanDistanceTransform MPSImageFeatureChannelFormat MPSImageFindKeypoints MPSImageGaussianBlur MPSImageGaussianPyramid MPSImageGuidedFilter MPSImageHistogram MPSImageHistogramEqualization MPSImageHistogramInfo MP...
() Citation Context ...n admits a Kashin’s representation of level C with V; (b) the matrix V satisfies B(0, √ M/C) ⊂ VQM . Random matrices V with i.i.d. subgaussian entries satisfy the above property with high probability =-=[16, 15, 14]-=-, which is why we ...