In this letter, we proposed a new algorithm to solve the problem concerning the direction-of-arrivals (DOAs) estimation of coherently distributed sources based on the block sparse signal matrix uncertainty model of compressed sensing. Considering the measurement matrix corrupted by the unknown noise, the central DOA and the angular spread estimation may degrade considerably. But our method is r...

The goal is to acquire signals in R that are well approximated by sparse signals with k nonzero components, where k << n. The measurement process can be represented by an m× n matrix A, where m is roughly proportional to k rather than n. The recovery algorithm uses the sketch and a description of the measurement matrix to construct a signal approximation x̂ that has only O(k) nonzero components....

The goal is to acquire signals in R that are well approximated by sparse signals with k nonzero components, where k << n. The measurement process can be represented by an m× n matrix A, where m is roughly proportional to k rather than n. The recovery algorithm uses the sketch and a description of the measurement matrix to construct a signal approximation x̂ that has only O(k) nonzero components....

Compressed sensing aims at recovering a sparse signal x ∈ RN from few nonadaptive, linear measurements Φ(x) given by a measurement matrix Φ. One of the fundamental recovery algorithms is an `1 minimisation. In this paper we investigate the situation when our measurement Φ(x) is contaminated by arbitrary noise under the assumption that the matrix Φ satisfies the restricted isometry property. Thi...

Construction on the measurement matrix A is a central problem in compressed sensing. Although using random matrices is proven optimal and successful in both theory and applications. A deterministic construction on the measurement matrix is still very important and interesting. In fact, it is still an open problem proposed by T. Tao. In this paper, we shall provide a new deterministic constructi...

If a researcher applies the conventional tests of scale-level measurement invariance through multi-group confirmatory factor analysis of a PC matrix and MLE to test hypotheses of strong and full measurement invariance when the researcher has a rating scale response format wherein the item characteristics are different for the two groups of respondents, do these scale-level analyses reflect (or ...

Different amounts of nanoclay were incorporated into the acrylic resin matrix at 0, 1, 3, and 5 wt.% loadings. The coatings were applied on low carbon steel plates. Optical microscopy, sedimentation test, transmission electron microscopy, and X-ray diffraction were employed to investigate the dispersion of nanoclay in matrix. The corrosion resistance of coatings was evaluated by electrochemical...

Geometric Dilution of Precision (GDOP) is a coefficient for constellations of Global Positioning System (GPS) satellites. These satellites are organized geometrically. Traditionally, GPS GDOP computation is based on the inversion matrix with complicated measurement equations. A new strategy for calculation of GPS GDOP is construction of time series problem; it employs machine learning and artif...

Recent development in compressed sensing (CS) has revealed that the use of a special design of measurement matrix, namely the spatially-coupled matrix, can achieve the informationtheoretic limit of CS. In this paper, we consider the measurement matrix which consists of the spatially-coupled orthogonal matrices. One example of such matrices are the randomly selected discrete Fourier transform (D...

This paper proposes a technique for recovering 3-D wide range human motions employing a set of uncaliblated mobile cameras. This paper also claims availability of such 3-D recovery in analyzing human motions. Three video cameras mounted on a mobile frame track and capture a human motion in a large field from three different directions. Feature points on the subject are registered in a measureme...