Results 231 to 240 of about 1,104,970 (268)

A practical solution for a large sparse matrix

Software: Practice and Experience, 1988
AbstractThis paper describes a computational technique that was used for determining whether a certain matrix equation, Mx = b, had an exact solution. Here, MT was a sparse 96,208 × 40,040 integer matrix. The approach is an appropriate alternative for certain matrices when memory constraints preclude using conventional techniques.
Irvin Roy Hentzel, David J. Pokrass
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The Solution of Large Symmetric Eigenproblems by Sectioning

SIAM Journal on Numerical Analysis, 1972
When a relatively few eigenvalues are desired for a very large symmetric matrix eigenvalue problem, direct methods such as Householder reduction tend to be inefficient. Inverse iteration works reasonably well but runs into difficulties when eigenvalues are clustered.
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A minimization method for the solution of large symmetriric eigenproblems

International Journal of Computer Mathematics, 1998
This paper concerns with the solution of a special eigenvalue problem for a large sparse symmetric matrix by a fast convergent minimization method. A theoretical analysis of the method is developed; it is proved that is convergent with a convergence rate of fourth order.
GALLIGANI, Emanuele, V. RUGGIERO, ZANNI, Luca   +2 more
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Large Deviations for Solutions of Stochastic Equations

Theory of Probability & Its Applications, 1996
Let \(D([0,T]; R^d)\) be a Skorokhod space, \(\mu^\varepsilon(A)=P\{\xi^\varepsilon(\cdot)\in A\}\), \(A\in {\mathcal B}(D([0,T]; R^d))\), \(\varepsilon > 0\), be a family of probability measures, corresponding to the \(d\)-dimensional locally infinitely divisible processes \(\xi^\varepsilon(t)\), \(t\geq 0\), \(\varepsilon > 0\), defined on some ...
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Production of large-scale peptides in solution

Biochemical Society Transactions, 1990
The production of large-scale peptides in solution has some advantages and some disadvantages. Advantages. (i) The layout of the synthesis can be planned in advance in respect of: main- and side-chain protection; fragment selection and methods of fragment coupling to minimize racemization.
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Process Simulation - From Large Computers and Small Solutions to Small Computers and Large Solutions

Chemical Product and Process Modeling, 2006
This paper reviews the evolution of process simulation in conjunction with the evolution of computer hardware and software technologies from a chemical engineering perspective. A brief history of this hardware evolution is presented and points to exponential growth of computing power.
William Y Svrcek, Marco A Satyro
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Large and entire large solution for a quasilinear problem

Nonlinear Analysis: Theory, Methods & Applications, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Uniqueness of large positive solutions

Zeitschrift für angewandte Mathematik und Physik, 2017
Let \(\Omega\) be a smooth bounded domain in \({\mathbb R}^N\). This paper is concerned with the uniqueness of blow-up boundary solutions for the logistic-type equation \(-\Delta u=\lambda u-a(x)f(u)\) in \(\Omega\), where \(\lambda\) is a real parameter, \(a\) is a non-negative potential, and \(f\) is a non-decreasing function that is super ...
Julián López-Gómez, Luis Maire
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Iterative solution of large structures

Computers & Structures, 1990
Abstract A general theory of iterative methods is developed for the analysis of large linear structures. The concepts of elimination and iteration are combined in order to make an efficient analysis of large structures feasible with microcomputers. It is shown that standard moment distribution methods of Cross ( Proc. struct. Div., ASCE 96 , 1–156,
A. Behravesh, A. Kaveh
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Parallel Solution of Large Scale Quadratic Programs

1998
We consider the solution of large and sparse linearly constrained quadratic programming problems. We describe an iterative scheme that requires to solve at each iteration a linear complementarity problem. For the solution of this last problem we examine parallel iterative solvers based on splittings of the complementarity matrix.
GALLIGANI, Emanuele, V. RUGGIERO, ZANNI, Luca   +2 more
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