Results 251 to 260 of about 92,081 (302)
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Applied Mathematics and Computation, 2011
Some properties of the matricial expression of the Fourier-Wiener transform are considered. Here the referred properties are a composition formula, Parceval formula and an inversion formula which is the extension an unitary explicit integral representation of the second quantization for one integral operator of the Wiener transform.
Nácere Hayek +2 more
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Some properties of the matricial expression of the Fourier-Wiener transform are considered. Here the referred properties are a composition formula, Parceval formula and an inversion formula which is the extension an unitary explicit integral representation of the second quantization for one integral operator of the Wiener transform.
Nácere Hayek +2 more
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Analysis, 1986
Summary: Let a probability space (\(\Omega\),\(\Sigma\),P) and sequences of r.v.'s \((X_ n(\omega))_ 1^{\infty}\), \((Y_ n(\omega))_ 1^{\infty}\), and a matrix of r.v.'s \(A=(A_{nk}(\omega))^{\infty}_{n,k=1}\) be given. We ask for the exact conditions for A which guarantee that each sequence \((X_ n(\omega))_ 1^{\infty}\), which is a.s. an element of \(
Stadtmüller, U., Trautner, Rolf
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Summary: Let a probability space (\(\Omega\),\(\Sigma\),P) and sequences of r.v.'s \((X_ n(\omega))_ 1^{\infty}\), \((Y_ n(\omega))_ 1^{\infty}\), and a matrix of r.v.'s \(A=(A_{nk}(\omega))^{\infty}_{n,k=1}\) be given. We ask for the exact conditions for A which guarantee that each sequence \((X_ n(\omega))_ 1^{\infty}\), which is a.s. an element of \(
Stadtmüller, U., Trautner, Rolf
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Matrix transformations between sequence spaces of generalized weighted means
Applied Mathematics and Computation, 2004 The main object of this paper is to introduce and study some sequence spaces which arise from concept of weighted means, determine their beta-duals and characterize matrix transformations between them. (C) 2002 Elsevier Inc.
E Malkowsky
exaly +2 more sources
The Matrix Transform Processor
IEEE Transactions on Computers, 1976A matrix transform processor (MTP) for an Evans and Sutherland LDS-2 graphics system has been designed and built at the University of North Carolina. The MTP performs all the important functions of a matrix multiplier, clipper, and perspective divider.
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Periodica Mathematica Hungarica, 1982
Let \(\delta\) be the space of all sequences \((x_ n)_{n\in {\mathbb{N}}}\) for which \(| x_ n|^{1/n}\to 0\) as \(n\to \infty\). The matrices \(A=[a_{ij}]_{i,j\in {\mathbb{N}}}\) are characterized which define a matrix transformation \(A:\ell^ 1\to \delta\). The main theorem and its proof are improvements of results of \textit{K. C. Rao}, Glasg.
Gupta, M., Kamthan, P. K.
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Let \(\delta\) be the space of all sequences \((x_ n)_{n\in {\mathbb{N}}}\) for which \(| x_ n|^{1/n}\to 0\) as \(n\to \infty\). The matrices \(A=[a_{ij}]_{i,j\in {\mathbb{N}}}\) are characterized which define a matrix transformation \(A:\ell^ 1\to \delta\). The main theorem and its proof are improvements of results of \textit{K. C. Rao}, Glasg.
Gupta, M., Kamthan, P. K.
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Boletín de la Sociedad Matemática Mexicana, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
O. E. Yaremko, K. R. Zababurin
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
O. E. Yaremko, K. R. Zababurin
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Proceedings 1989 IEEE International Conference on Computer Design: VLSI in Computers and Processors, 2003
The matrix transform chip (MTC) is designed to perform matrix computations of the form Y=UDV where D is the input data matrix of 16-bit twos complement fixed-point numbers and U, V, are arbitrary coefficient matrices of the same precision. The data matrix D is input to the chip in raster scanned order at a maximum sample rate of 40 MHz, and the output ...
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The matrix transform chip (MTC) is designed to perform matrix computations of the form Y=UDV where D is the input data matrix of 16-bit twos complement fixed-point numbers and U, V, are arbitrary coefficient matrices of the same precision. The data matrix D is input to the chip in raster scanned order at a maximum sample rate of 40 MHz, and the output ...
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Group Convolutions and Matrix Transforms
SIAM Journal on Algebraic Discrete Methods, 1987Given a finite group G (possibly noncommutative) and a field \({\mathbb{F}}\), group convolutions are constructed based on the group algebra of G over \({\mathbb{F}}\). Matrices with entries in the group algebra are constructed so that they have a convolution property relative to G.
Eberly, David, Hartung, Paul
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Pericellular Matrix in Malignant Transformation
1982Publisher Summary This chapter describes the properties of the major defined matrix components, and considers their role for the cell phenotype. The principal function of the matrix is to give mechanical support and to anchor cells in tissue type-specific structures, but it may also have other duties, such as that of a selective permeability barrier.
K, Alitalo, A, Vaheri
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