Matrix Algorithms in MATLAB by Tongru Huo

Matrix Algorithms in MATLAB Tongru Huo ebook
Page: 750
Format: pdf
ISBN: 9780128038048
Publisher: Elsevier Science

May 2, 2013 - 8 min - Uploaded by Anand VyasPlease watch the above videoclip in HD (720p) option. Try MATLAB, Simulink, and Other Products. This paper describes the results of a project to interface MATLAB with a parallel Interfacing MATLAB with a parallel virtual processor for matrix algorithms. In MuPAD Notebook only, transpose(A) returns the transpose At of the matrix A. This MATLAB function sets one or more of the tunable parameters used in the Also produces very detailed information about the sparse matrix algorithms. There are a number of ways to compute the rank of a matrix. The algorithm first finds a pseudoperipheral vertex of the graph of the matrix. It uses block algorithms, which operate on several columns of a matrix at a time. I know that there are some clever algorithms to exploit the fact that the matrix is sparse "Never" invert a matrix, particularly a large sparse one. This MATLAB function constructs an adaptive algorithm object based on the property that represents the inverse correlation matrix for the RLS algorithm. Having trouble coming up with a code that multiplies two matrices together. Function C = strassen(A, B, nmin) %STRASSEN Strassen's fast matrix multiplication algorithm. Higham, "A Schur-Parlett algorithm for computing matrix functions," SIAM J. Ziggurat algorithm generates normally distributed random numbers. Orth uses the classic Gram-Schmidt orthogonalization algorithm.