This paper introduces and analyzes a new parallel-in-time gradient type method for the solution of convex linear-quadratic discrete-time optimal control (DTOC) problems. Each iteration of the classical gradient method requires the solution of the forward-in-time state equation followed by the solution of the backward-in-time adjoint equation to compute the gradient. To introduce parallelism, th...

We have recently proposed a manifold-based trust-region method to compute extreme eigenpairs of symmetric matrix pencils [3]. The general optimization method had been shown [1, 2] to enjoy strong global and local convergence properties, which are inherited by its ”brute force” application to the extreme eigenproblem. However, the trust-region mechanism, which restricts the norm of the update in...

The classical Newton iteration method for matrices can be modified into an efficient algorithm when structured matrices are involved. The difficulty, however, is the importance of the choice of the starting matrix. In this paper, we propose a new initial iteration step which makes the choice of the starting matrix less critical. The validity of the approach is illustrated by numerical experiments.

This paper deals with a modification of the Hill cipher. In this, we have introduced interweaving in each step of the iteration. The interweaving of the resulting plaintext, at each stage of the iteration, and the multiplication with the key matrix leads to confusion and diffusion. From the cryptanalysis performed in this investigation, we have found that the cipher is a strong one.

this paper introduces a new method for accelerating current sluggish fem and improving memory demand in fem problems with high node resolution or bulky structures. like most of the numerical methods, fem results to a matrix equation which normally has huge dimension. breaking the main matrix equation into several smaller size matrices, the solving procedure can be accelerated. for implementing ...

For the orthogonal direction algorithm, the iteration direction is the direction vector, and the iteration error of the adaptive filter is caused by the input vector. These two directions are not the same one, which leads to more deviation for the iteration error. In this paper, an orthogonal direction algorithm using direction error is presented to settle this problem, which the iteration erro...

In this paper, we introduce a new iteration process for approximation of common fixed point of countably infinite family of nonself asymptotically nonexpansive mappings in uniformly convex Banach spaces, and prove weak and strong convergence of our iteration process to a common fixed point of these operators. Our theorems extend, generalize and unify many recently announced results. Our iterati...

in this paper, we represent an inexact inverse subspace iteration method for com- puting a few eigenpairs of the generalized eigenvalue problem ax = bx[q. ye and p. zhang, inexact inverse subspace iteration for generalized eigenvalue problems, linear algebra and its application, 434 (2011) 1697-1715 ]. in particular, the linear convergence property of the inverse subspace iteration is preserved.

In this work, we propose a new approach for efficient edgepreserving image deconvolution. Our algorithm is based on a novel type of explicit image filter guided filter. The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter, but has better behaviors near edges. We propose an efficient iterative algorithm with the decouple of deblurring and denoi...