In this paper, we examine the space discretization of time fractional telegraph equation (TFTE) with Mamadu-Njoseh orthogonal basis functions. For ease and convenience, we deal with the fractional derivative by first ...In this paper, we examine the space discretization of time fractional telegraph equation (TFTE) with Mamadu-Njoseh orthogonal basis functions. For ease and convenience, we deal with the fractional derivative by first converting from Caputo’s type to Riemann-Liouville’s type. The proposed method was constrained to precise error analysis to establish the accuracy of the method. Numerical experimentation was implemented with the aid of MAPLE 18 to show convergence of the method as compared with the analytic solution.展开更多
Parallel algorithms have been designed for the past 20 years initially by parallelising existing sequential algorithms for many different parallel architectures. More recently parallel strategies have been identified ...Parallel algorithms have been designed for the past 20 years initially by parallelising existing sequential algorithms for many different parallel architectures. More recently parallel strategies have been identified and utilized 'resulting in many new parallel algorithms. However the analysis of such algorithms reveals that further strategies can be applied to increase the parallelism. One of these, i.e., increasing the computational capacity in each processing node can reduce the congestion/communicgtion for shared memory/distributed memory multiprocessor systems and dramahcally improve the Performance of the algorithm. Two algorithms are identified and studied, i.e., the Cyclic reduction method for solving large tridiagonal linear systems in which the odd/even sequence is increased to a 'stride of 3' or more resulting in an improved algorithm. Similarly the Gaussian Elimination method for solving linear systems in which one element is eliminated at a time can be adapted to parallel form in which two elements are simultaneously eliminated resulting in the Parallel Implicit Elimination (P.I.E.) method. Numerical results are presented to support the analyses.展开更多
We study the constrained systemof linear equations Ax=b,x∈R(A^(k))for A∈C^(n×n)and b∈Cn,k=Ind(A).When the system is consistent,it is well known that it has a unique A^(D)b.If the system is inconsistent,then we...We study the constrained systemof linear equations Ax=b,x∈R(A^(k))for A∈C^(n×n)and b∈Cn,k=Ind(A).When the system is consistent,it is well known that it has a unique A^(D)b.If the system is inconsistent,then we seek for the least squares solution of the problem and consider min_(x∈R(A^(k)))||b−Ax||2,where||·||2 is the 2-norm.For the inconsistent system with a matrix A of index one,it was proved recently that the solution is A^(■)b using the core inverse A^(■)of A.For matrices of an arbitrary index and an arbitrary b,we show that the solution of the constrained system can be expressed as A^(■)b where A^(■)is the core-EP inverse of A.We establish two Cramer’s rules for the inconsistent constrained least squares solution and develop several explicit expressions for the core-EP inverse of matrices of an arbitrary index.Using these expressions,two Cramer’s rules and one Gaussian elimination method for computing the core-EP inverse of matrices of an arbitrary index are proposed in this paper.We also consider the W-weighted core-EP inverse of a rectangular matrix and apply the weighted core-EP inverse to a more general constrained system of linear equations.展开更多
文摘In this paper, we examine the space discretization of time fractional telegraph equation (TFTE) with Mamadu-Njoseh orthogonal basis functions. For ease and convenience, we deal with the fractional derivative by first converting from Caputo’s type to Riemann-Liouville’s type. The proposed method was constrained to precise error analysis to establish the accuracy of the method. Numerical experimentation was implemented with the aid of MAPLE 18 to show convergence of the method as compared with the analytic solution.
文摘Parallel algorithms have been designed for the past 20 years initially by parallelising existing sequential algorithms for many different parallel architectures. More recently parallel strategies have been identified and utilized 'resulting in many new parallel algorithms. However the analysis of such algorithms reveals that further strategies can be applied to increase the parallelism. One of these, i.e., increasing the computational capacity in each processing node can reduce the congestion/communicgtion for shared memory/distributed memory multiprocessor systems and dramahcally improve the Performance of the algorithm. Two algorithms are identified and studied, i.e., the Cyclic reduction method for solving large tridiagonal linear systems in which the odd/even sequence is increased to a 'stride of 3' or more resulting in an improved algorithm. Similarly the Gaussian Elimination method for solving linear systems in which one element is eliminated at a time can be adapted to parallel form in which two elements are simultaneously eliminated resulting in the Parallel Implicit Elimination (P.I.E.) method. Numerical results are presented to support the analyses.
文摘We study the constrained systemof linear equations Ax=b,x∈R(A^(k))for A∈C^(n×n)and b∈Cn,k=Ind(A).When the system is consistent,it is well known that it has a unique A^(D)b.If the system is inconsistent,then we seek for the least squares solution of the problem and consider min_(x∈R(A^(k)))||b−Ax||2,where||·||2 is the 2-norm.For the inconsistent system with a matrix A of index one,it was proved recently that the solution is A^(■)b using the core inverse A^(■)of A.For matrices of an arbitrary index and an arbitrary b,we show that the solution of the constrained system can be expressed as A^(■)b where A^(■)is the core-EP inverse of A.We establish two Cramer’s rules for the inconsistent constrained least squares solution and develop several explicit expressions for the core-EP inverse of matrices of an arbitrary index.Using these expressions,two Cramer’s rules and one Gaussian elimination method for computing the core-EP inverse of matrices of an arbitrary index are proposed in this paper.We also consider the W-weighted core-EP inverse of a rectangular matrix and apply the weighted core-EP inverse to a more general constrained system of linear equations.
