Increase of accuracy in solving differential equations with singularities of the type by a right choice of an additional term
Increase of iteration's order.
Incremental unknowns for solving partial differential equations.
Incremental unknowns method and compact schemes
Incremental unknowns on nonuniform meshes
Indefinite integration of oscillatory functions
A simple and fast algorithm is presented for evaluating the indefinite integral of an oscillatory function , -1 ≤ x < y ≤ 1, ω ≠ 0, where the Chebyshev series expansion of the function f is known. The final solution, expressed as a finite Chebyshev series, is obtained by solving a second-order linear difference equation. Because of the nature of the equation special algorithms have to be used to find a satisfactory approximation to the integral.
Index Transforms for Multidimensional DFT's and Convolutions.
Index Transforms for N-dimensional DFT's.
Index vector-function and minimal cycles.
Indicateurs d’erreur en version des éléments spectraux
Individual Cell-Based Model for In-Vitro Mesothelial Invasion of Ovarian Cancer
In vitro transmesothelial migration assays of ovarian cancer cells, isolated or aggregated in multicellular spheroids, are reproduced deducing suitable Cellular Potts Models (CPM). We show that the simulations are in good agreement with the experimental evidence and that the overall process is regulated by the activity of matrix metalloproteinases (MMPs) and by the interplay of the adhesive properties of the cells with the extracellular matrix and...
Inequalities of Ostrowski type and applications in numerical integration.
Inequalities of Ostrowski-Grüss type and applications
Some new inequalities of Ostrowski-Grüss type are derived. They are applied to the error analysis for some Gaussian and Gaussian-like quadrature formulas.
Inequality-based approximation of matrix eigenvectors
A novel procedure is given here for constructing non-negative functions with zero-valued global minima coinciding with eigenvectors of a general real matrix A. Some of these functions are distinct because all their local minima are also global, offering a new way of determining eigenpairs by local optimization. Apart from describing the framework of the method, the error bounds given separately for the approximation of eigenvectors and eigenvalues provide a deeper insight into the fundamentally...
Inequality-sum : a global constraint capturing the objective function
This paper introduces a new method to prune the domains of the variables in constrained optimization problems where the objective function is defined by a sum , and where the integer variables are subject to difference constraints of the form . An important application area where such problems occur is deterministic scheduling with the mean flow time as optimality criteria. This new constraint is also more general than a sum constraint defined on a set of ordered variables. Classical approaches...
Inequality-sum: a global constraint capturing the objective function
This paper introduces a new method to prune the domains of the variables in constrained optimization problems where the objective function is defined by a sum y = ∑xi, and where the integer variables xi are subject to difference constraints of the form xj - xi ≤ c. An important application area where such problems occur is deterministic scheduling with the mean flow time as optimality criteria. This new constraint is also more general than a sum constraint defined on a set of ordered variables....
Inertias and ranks of some Hermitian matrix functions with applications
Let S be a given set consisting of some Hermitian matrices with the same size. We say that a matrix A ∈ S is maximal if A − W is positive semidefinite for every matrix W ∈ S. In this paper, we consider the maximal and minimal inertias and ranks of the Hermitian matrix function f(X,Y) = P − QXQ* − TYT*, where * means the conjugate and transpose of a matrix, P = P*, Q, T are known matrices and for X and Y Hermitian solutions to the consistent matrix equations AX =B and YC = D respectively. As applications,...
Inexact Newton method under weak and center-weak Lipschitz conditions
The paper develops semilocal convergence of Inexact Newton Method INM for approximating solutions of nonlinear equations in Banach space setting. We employ weak Lipschitz and center-weak Lipschitz conditions to perform the error analysis. The results obtained compare favorably with earlier ones in at least the case of Newton's Method (NM). Numerical examples, where our convergence criteria are satisfied but the earlier ones are not, are also explored.
Inexact Newton methods and recurrent functions
We provide a semilocal convergence analysis for approximating a solution of an equation in a Banach space setting using an inexact Newton method. By using recurrent functions, we provide under the same or weaker hypotheses: finer error bounds on the distances involved, and an at least as precise information on the location of the solution as in earlier papers. Moreover, if the splitting method is used, we show that a smaller number of inner/outer iterations can be obtained. Furthermore, numerical...
Inexact Newton preconditioning techniques for large symmetric eigenvalue problems.