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ABSTRACT: To solve a class of nonlinear parameter estimation problems, a method combining the regularized structured nonlinear total
least norm (RSNTLN) method and parameter separation scheme is suggested. The method guarantees the convergence of parameters
and has an advantages in reducing the residual norm over the use of RSNTLN only.
Numerical experiments for two models appeared in signal processing show that the suggested method is more effective in obtaining
solution and parameter with minimum residual norm.
Journal of Applied Mathematics and Computing 04/2012; 22(1):373-385.
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ABSTRACT: We study convergence of multisplitting method associated with a block diagonal conformable multisplitting for solving a linear
system whose coefficient matrix is a symmetric positive definite matrix which is not an H-matrix. Next, we study the validity
ofm-step multisplitting polynomial preconditioners which will be used in the preconditioned conjugate gradient method.
Journal of Applied Mathematics and Computing 04/2012; 22(1):169-180.
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ABSTRACT: In this paper, we study the convergence of both the multisplitting method and the relaxed multisplitting method associated
with SOR or SSOR multisplittings for solving a linear system whose coefficient matrix is anM-matrix.
Journal of Applied Mathematics and Computing 01/2007; 24(1):273-282.
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ABSTRACT: The regularized structured total least norm (RSTLN) method finds an approximate solutionx and error matrixE to the overdetermined linear system (H+E)x≈b, preserving structure ofH. A new separation scheme by parts of variables for the regularized structured total least norm on blind deconvolution problem
is suggested. A method combining the regularized structured total least norm method with a separation by parts of variables
can be obtain a better approximated solution and a smaller residual. Computational results for the practical problem with
Block Toeplitz with Toeplitz Block structure show the new method ensures more efficiency on image restoration.
Journal of Applied Mathematics and Computing 02/2005; 19(1):151-164.
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ABSTRACT: We study convergence of symmetric multisplitting method associated with many different multisplittings for solving a linear
system whose coefficient matrix is a symmetric positive definite matrix which is not an H-matrix.
Journal of Applied Mathematics and Computing 02/2005; 18(1):59-72.
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ABSTRACT: In this paper, we study the convergence of both relaxed multisplitting method and nonstationary two-stage multisplitting method
associated with a multisplitting which is obtained from the ILU factorizations for solving a linear system whose coefficient
matrix is anH-matrix. Also, parallel performance results of nonstaionary two-stage multisplitting method using ILU factorizations as inner
splittings on the IBM p690 supercomputer are provided to analyze theoretical results.
Journal of Applied Mathematics and Computing 01/2004; 15(1):77-90.
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ABSTRACT: A method is proposed to predict the distances between given residue pairs (betweenC
α atoms) of a protein using a sequence to structure mapping by indefinite quadratic approximation. The prediction technique
requires a data fitting in three dimensional space with coordinates of the residues of known structured proteins and leads
to a numerical representation of 20 amino acids by minimizing a large least norm iteratively. These approximations are used
in distance prediction for given residue pairs. Some computational experience on a test set of small proteins from Brookhaven
Protein Data Bank are given.
Journal of Applied Mathematics and Computing 12/2002; 12(1):155-164.
