On the Sample Complexity of Multichannel Frequency Estimation via Convex Optimization

The use of multichannel data in line spectral estimation (or frequency estimation) is common for improving the estimation accuracy in array processing, structural health monitoring, wireless communications, and more. Recently proposed atomic norm methods have attracted considerable attention due to their provable superiority in accuracy, flexibility and robustness compared with conventional approaches. In this paper, we analyze atomic norm minimization for multichannel frequency estimation from noiseless compressive data, showing that the sample size per channel that ensures exact estimation decreases with the increase of the number of channels under mild conditions. In particular, given $L$ channels, order $K\left(\log K\right) \left(1+\frac{1}{L}\log N\right)$ samples per channel, selected randomly from $N$ equispaced samples, suffice to ensure with high probability exact estimation of $K$ frequencies that are normalized and mutually separated by at least $\frac{4}{N}$. Numerical results are provided corroborating our analysis.Comment: 14 pages, double column, to appear in IEEE Trans. Information Theor

A Novel Method of Multispectral Imagery Registration Based on Minor and Noise Component Criterion

AbstractFor multispectral imagery, spatial registration between bands is a very important part of the overall quality of the multispectral imagery product. In this paper, a multispectral imagery registration method is presented. It takes minor and noise component of sample covariance matrix as measure criterion, utilizes mutual information method to create registration seed sources, uses smooth filter to extend trapping width of registration curve. Experiments were conducted using multispectral imagery from the ETM Satellite. Control points optimal searching experiments show that the presented method can improve the efficiency and accuracy of multispectral imagery registration greatly

On Lazy Bin Covering and Packing problems

AbstractIn this paper, we study two interesting variants of the classical bin packing problem, called Lazy Bin Covering (LBC) and Cardinality Constrained Maximum Resource Bin Packing (CCMRBP) problems. For the offline LBC problem, we first prove the approximation ratio of the First-Fit-Decreasing and First-Fit-Increasing algorithms, then present an APTAS. For the online LBC problem, we give a competitive analysis for the algorithms of Next-Fit, Worst-Fit, First-Fit, and a modified HARMONICM algorithm. The CCMRBP problem is a generalization of the Maximum Resource Bin Packing (MRBP) problem Boyar et al. (2006) [1]. For this problem, we prove that its offline version is no harder to approximate than the offline MRBP problem

Geometric Spanner of Segments (Algorithms and Computation)

Algorithms and computation : 18th International Symposium, ISAAC 2007, Sendai, Japan, December 17-19, 2007 : proceedings ; ISAAC 2007 : (Lecture notes in computer science ; 4835)Proc. of ISACCGeometric spanner is a fundamental structure in computational geometry and plays an important role in many geometric networks design applications. In this paper, we consider a generalization of the classical geometric spanner problem (called segment spanner): Given a set S of disjoint 2-D segments, find a spanning network G with minimum size so that for any pair of points in S, there exists a path in G with length no more than t times their Euclidean distance. Based on a number of interesting techniques (such as weakly dominating set, strongly dominating set, and interval cover), we present an efficient algorithm to construct the segment spanner. Our approach first identifies a set of Steiner points in S, then construct a point spanner for them. Our algorithm runs in O(|Q| + n 2 logn) time, where Q is the set of Steiner points. We show that Q is an O(1)-approximation in terms of its size when S is relatively “well” separated by a constant. For arbitrary rectilinear segments under L 1 distance, the approximation ratio improves to 2

The Metabolism of Baicalin in Rat and the Biological Activities of the Metabolites

Baicalin is one of the major bioactive constituents of Scutellariae Radix, but the biotransformation of it is poorly understood. In this paper, the metabolism of baicalin in rat was studied. Nine metabolites including one new compound were isolated and identified structurally. The plausible scheme for the biotransformation pathways of baicalin in the rats was deduced. And the main metabolites were evaluated for their antioxidation and anti-inflammation biological activities for the first time

An ant colony optimization method for generalized TSP problem

Focused on a variation of the euclidean traveling salesman problem (TSP), namely, the generalized traveling salesman problem (GTSP), this paper extends the ant colony optimization method from TSP to this field. By considering the group influence, an improved method is further improved. To avoid locking into local minima, a mutation process and a local searching technique are also introduced into this method. Numerical results show that the proposed method can deal with the GTSP problems fairly well, and the developed mutation process and local search technique are effective

Kriging analysis on CPTU data from offshore wind farm

publishedVersio