Matrix Algorithms in MATLAB. Tongru Huo

Matrix Algorithms in MATLAB


Matrix.Algorithms.in.MATLAB.pdf
ISBN: 9780128038048 | 750 pages | 19 Mb


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Matrix Algorithms in MATLAB Tongru Huo
Publisher: Elsevier Science



Std2 computes the standard deviation of the array A using std(A(:)) . Try MATLAB, Simulink, and Other Products. This example shows the value of using sparse arithmetic when you have a sparse problem. Tensor manipulations that can be used for fast algorithm prototyping. The tensor class four MATLAB classes for manipulating tensors: tensor, tensor as matrix,. The algorithm first finds a pseudoperipheral vertex of the graph of the matrix. This is much faster than x=A\b for large matrices. Using a matrix from the MATLAB Gallery collection as an example, this article discusses three variants of the QR algorithm available in MATLAB. May 2, 2013 - 8 min - Uploaded by Anand VyasPlease watch the above videoclip in HD (720p) option. The matrix has n rows, where you choose n to be a large value. Function C = strassen(A, B, nmin) %STRASSEN Strassen's fast matrix multiplication algorithm. The algorithm will check to see if A is symmetric and use a more efficient algorithm if it is. This MATLAB function returns the inverse of the square matrix X. One option is the sample matrix inversion (SMI) algorithm. Det computes the determinant from the triangular factors obtained by Gaussian elimination with the lu function.





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