The null space property and the restricted isometry property for a measurement matrix are two basic properties in compressive sampling, and are closely related to the sparse approximation. In this paper, we introduce the sparse approximation property of order s for a measurement matrix A: ‖xs‖2 ≤ D‖Ax‖2 + β σs(x) √ s for all x, where xs is the best s-sparse approximation of the vector x in `, σ...

With a short linear array configured in the cross-track direction, downward looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) can obtain the 3-D image of an imaging scene. To improve the cross-track resolution, sparse recovery methods have been investigated in recent years. In the compressive sensing (CS) framework, the reconstruction performance depends on ...

The novel theory of Compressed Sensing (CS) reduces the samples of compressible signal sharply by information sampling. In order to improve reconstruction accuracy of noise signal for CS, a Singular Value Decomposition (SVD) noise signal reconstruction algorithm is presented in this paper. This algorithm decomposes the random measurement matrix, modifies the diagonal matrix Eigen values by mean...

Abstract. The measurement matrix employed in compressive sensing typically cannot be known precisely a priori, and must be estimated via calibration. One may take multiple compressive measurements, from which the measurement matrix and underlying signals may be estimated jointly. This is of interest as well when the measurement matrix may change as a function of the details of what is measured....

Compressive sensing (CS) has been a way to lower sampling rate leading to data reduction for processing in multiple-input multiple-output (MIMO) radar systems. In this paper, we further reduce the computational complexity of a pulse-Doppler collocated MIMO radar by introducing a two-dimensional (2D) compressive sensing. To do so, we first introduce a new 2D formulation for the compressed receiv...

The emergence of compressed sensing (CS) theory provides potential hardware architecture to sub-Nyquist sample the wideband signals. However, applying this discrete CS model to continuous analogue signals is not an easy task. The modulated wideband converter (MWC) is an efficient wideband compressed sampling architecture for the sparse multiband signals. In this paper, a soft-calibration system...

BACKGROUND AND PURPOSE The aim of this study was to assess the effect of zero-filled interpolation (ZIP) on measurements of the cervical arteries because its benefits on the accuracy and precision of measurements in medium-sized arteries remains unknown. METHODS Three observers measured 36 computer-simulated vessels (2-6.8 mm) and 130 normal cervical vessels (assessed with two-dimensional tim...

In this study, the stochastic restricted and unrestricted two-parameter estimators of fixed and random effects are investigated in the linear mixed measurement error models. For this purpose, the asymptotic properties and then the comparisons under the criterion of mean squared error matrix (MSEM) are derived. Furthermore, the proposed methods are used for estimating the biasing parameters. Fin...

this paper presents a method for identification of linear system physical parameters (structural mass, damping and stiffness matrices) using the inverse solution of equation of motion in the frequency domain, by focus on the reducing the illconditioning effect. the method utilizes the measured responses from the forced vibration test of structure in order to identify the system properties and d...

application of automatic systems, including discharge measurement technology is one of the effective methods for improving delivery management, water use efficiency, flexibility, and performance of irrigation networks. several aspects such as hydraulic, technical, physical, environmental, economic, social, and managerial, have significant impact on these systems selection. due to diversity of t...