This paper aims to reconstruct the internal structure of a two-dimensional test object via numerically simulated full-wave time domain radar tomography with presence wavelength-induced (WI) uncertainties, following from complex structure, and diameters 21 or 64 times wavelength signal propagating inside target. In particular, we consider an application in planetary scientific studies reconstruc...

Biometric-based identity authentication is integral to modern-day technologies. From smart phones, personal computers, and tablets security checkpoints, they all utilize a form of check based on methods such as face recognition fingerprint-verification. Photoplethysmography (PPG) another biometric-based that has recently been gaining momentum, because it effective easy implement. This paper con...

disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. therefore, in this paper a disguised face recognition algorithm based on local phase quantization (lpq) method and singular value decomposition (svd) is presented which deals with two main challenges. the first challenge is when an individual intentionally alters the appearance ...

The singular value decomposition (SVD) is a generalization of the eigen-decomposition which can be used to analyze rectangular matrices (the eigen-decomposition is definedonly for squaredmatrices). By analogy with the eigen-decomposition, which decomposes a matrix into two simple matrices, the main idea of the SVD is to decompose a rectangular matrix into three simple matrices: Two orthogonal m...

Myocardial ischemia is one of the leading causes of morbidity and mortality in the western countries. It is of importance to efficiently and accurately detect and localize ischemia in the early stage. The solution of the inverse problem of electrocardiography provides a promising noninvasive approach for the localization of ischemic areas. However, the general electrode configuration of multich...

Quantification of cerebral blood flow (CBF) and the tissue residue function (R) using bolus-tracking MRI requires deconvolution of the arterial input function (AIF). Currently, the most commonly used deconvolution method is singular value decomposition (SVD), which has been shown to produce accurate estimations of CBF. However, this method introduces unwanted oscillations in the time course of ...

other fields. However, the spectral properties of the Laplace Transform tend to complicate its numerical treatment; therefore, the closely related “Truncated” Laplace Transforms are often used in applications. We have constructed efficient algorithms for the evaluation of the Singular Value Decomposition (SVD) of Truncated Laplace Transforms; in the current paper, we introduce algorithms for th...

One of directions in the development Lomov’s regularization method is approach related to holomorphic singularly perturbed problems, which allows one construct solutions such problems form series powers a small parameter that converge usual sense. For boundary-value problem pseudo-holomorphic continuation very urgent. In this paper, we examine for Tikhonov system and give conditions existence i...

Introduction. Dynamic Susceptibility Contrast – Magnetic Resonance Imaging (DSC-MRI) allows to quantify Cerebral Blood Flow (CBF), Volume (CBV) and Mean Transit Time (MTT) by measuring Arterial Input Function AIF(t) and tissue concentration C(t) and estimating by deconvolution the tissue Residue function R(t): ( ) [ ( ) ( )] C t CBF AIF t R t = ⋅ ⊗ (eq.1). Singular Value Decomposition (SVD) [1]...

The Cauchy problem for Helmholtz equation arises from inverse scattering problems. Specific backgrounds can be seen in the existing literature; we can refer to 1–6 and so forth. A number of numerical methods for stabilizing this problem are developed. Several boundary element methods combined with iterative, conjugate gradient, Tikhonov regularization, and singular value decomposition methods a...