Matrix Algorithms in MATLAB by Tongru Huo

Matrix Algorithms in MATLAB



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


Std2 computes the standard deviation of the array A using std(A(:)) . This paper describes the results of a project to interface MATLAB with a parallel Interfacing MATLAB with a parallel virtual processor for matrix algorithms. I need to write a recursive function to calculate the determinant of a square matrix. Works entirely with the original matrix. Try MATLAB, Simulink, and Other Products. The trust-region algorithm requires that you supply the gradient in fun formula for updating the approximation of the Hessian matrix. Orth uses the classic Gram-Schmidt orthogonalization algorithm. Both incorporate several improvements over previous algorithms. Supply a positive definite correlation matrix, R , for estimating the spectral density . This is primarly due to the simpler memory stucture of a full matrix which allows for the extended optimization of the matrix-vector algorithms. Det computes the determinant from the triangular factors obtained by Gaussian elimination with the lu function. May 2, 2013 - 8 min - Uploaded by Anand VyasPlease watch the above videoclip in HD (720p) option. Please am finding it difficult to modify the code to enable the strassen algorithm applicable for odd dimensions. Array indexing, concatenation, sorting, and reshaping. Function C = strassen(A, B, nmin) %STRASSEN Strassen's fast matrix multiplication algorithm. This MATLAB function returns the inverse of the square matrix X.





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