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270,257
An iterative method for the solution of the eigenvalue problem of linear differential and integral
, 1950
"... The present investigation designs a systematic method for finding the latent roots and the principal axes of a matrix, without reducing the order of the matrix. It is characterized by a wide field of applicability and great accuracy, since the accumulation of rounding errors is avoided, through the ..."
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Cited by 537 (0 self)
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the process of "minimized iterations". Moreover, the method leads to a well convergent successive approximation procedure by which the solution of integral equations of the Fredholm type and the solution of the eigenvalue problem of linear differential and integral operators may be accomplished. I.
Hierarchical Modelling and Analysis for Spatial Data. Chapman and Hall/CRC,
, 2004
"... Abstract Often, there are two streams in statistical research one developed by practitioners and other by main stream statisticians. Development of geostatistics is a very good example where pioneering work under realistic assumptions came from mining engineers whereas it is only now that statisti ..."
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Cited by 442 (45 self)
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in There is no doubt that the availability of cheap and powerful computers has increased the interest in ML applications. With spatially correlated data, the maximization of the likelihood requires considerable computer power mainly for two numerical operations: matrix inversion and maximization in multidimensional
LevelSpacing Distributions and the Airy Kernel
 COMMUNICATIONS IN MATHEMATICAL PHYSICS
, 1994
"... Scaling levelspacing distribution functions in the "bulk of the spectrum" in random matrix models of N x N hermitian matrices and then going to the limit N — » oo leads to the Fredholm determinant of the sine kernel sinπ(x — y)/π(x — y). Similarly a scaling limit at the "edge o ..."
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Cited by 430 (24 self)
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Scaling levelspacing distribution functions in the "bulk of the spectrum" in random matrix models of N x N hermitian matrices and then going to the limit N — » oo leads to the Fredholm determinant of the sine kernel sinπ(x — y)/π(x — y). Similarly a scaling limit at the &
Numerical Solution of Fractional Control System by Haarwavelet Operational Matrix Method
, 2016
"...  Abstract In recent years, there has been greater attempt to find numerical solutions of differential equations using wavelet's methods. The following method is based on vector forms of Haarwavelet functions. In this paper, we will introduce one dimensional Ha ..."
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Haarwavelet functions and the Haarwavelet operational matrices of the fractional order integration. Also the Haarwavelet operational matrices of the fractional order differentiation are obtained. Then we propose the Haarwavelet operational matrix method to achieve the Haarwavelet time response
An operational Haar wavelet method for solving fractional Volterra integral equations
 International Journal of Applied Mathematics and Computer Science 21(3): 535–547, DOI
, 2011
"... A Haar wavelet operational matrix is applied to fractional integration, which has not been undertaken before. The Haar wavelet approximating method is used to reduce the fractional Volterra and Abel integral equations to a system of algebraic equations. A global error bound is estimated and some num ..."
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Cited by 4 (0 self)
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A Haar wavelet operational matrix is applied to fractional integration, which has not been undertaken before. The Haar wavelet approximating method is used to reduce the fractional Volterra and Abel integral equations to a system of algebraic equations. A global error bound is estimated and some
An Operational Haar Wavelet Method for Solving Fractional Volterra Integral Equations
, 2009
"... In this work, the Haar wavelet operational matrix of fractional integration is first obtained. Haar wavelet approximating method is then utilized to reduce the fractional Volterra integral equations (which are also called the weaklysingular linear Volterra integral equations) and in particular the ..."
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In this work, the Haar wavelet operational matrix of fractional integration is first obtained. Haar wavelet approximating method is then utilized to reduce the fractional Volterra integral equations (which are also called the weaklysingular linear Volterra integral equations) and in particular
The factorized Smatrix of CFT/AdS
, 2004
"... We argue that the recently discovered integrability in the largeN CFT/AdS system is equivalent to diffractionless scattering of the corresponding hidden elementary excitations. This suggests that, perhaps, the key tool for finding the spectrum of this system is neither the gauge theory’s dilatati ..."
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Cited by 240 (7 self)
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dilatation operator nor the string sigma model’s quantum Hamiltonian, but instead the respective factorized Smatrix. To illustrate the idea, we focus on the closed fermionic su(11) sector of the N = 4 gauge theory. We introduce a new technique, the perturbative asymptotic Bethe ansatz, and use
Region Covariance: A Fast Descriptor for Detection And Classification
 In Proc. 9th European Conf. on Computer Vision
, 2006
"... We describe a new region descriptor and apply it to two problems, object detection and texture classification. The covariance of dfeatures, e.g., the threedimensional color vector, the norm of first and second derivatives of intensity with respect to x and y, etc., characterizes a region of in ..."
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Cited by 278 (14 self)
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of interest. We describe a fast method for computation of covariances based on integral images. The idea presented here is more general than the image sums or histograms, which were already published before, and with a series of integral images the covariances are obtained by a few arithmetic operations
Analysis of Singular Systems using the Haar Wavelet Transform
"... Abstract: In this paper the application of Haar wavelets is investigated in the problem of determining the trajectory sensitivity function of singular systems. It is shown that the corresponding differentialalgebraic system equation could be converted to an algebraic generalized Lyapunov equation t ..."
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Abstract: In this paper the application of Haar wavelets is investigated in the problem of determining the trajectory sensitivity function of singular systems. It is shown that the corresponding differentialalgebraic system equation could be converted to an algebraic generalized Lyapunov equation
The SegmentedMatrix Algorithm for Haar Discrete Wavelet Transform
"... Discrete wavelet transform (DWT) is an efficient tool for multiresolution decomposition of images. It has been shown to be very promising due to its high compression ratio and selfsimilar data structure. Conventionally a 2D DWT is accomplished by performing two 1D operations: one along the rows ..."
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Discrete wavelet transform (DWT) is an efficient tool for multiresolution decomposition of images. It has been shown to be very promising due to its high compression ratio and selfsimilar data structure. Conventionally a 2D DWT is accomplished by performing two 1D operations: one along the rows
Results 1  10
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270,257