Matrix Algorithms in MATLAB Tongru Huo
Publisher: Elsevier Science

The tensor class four MATLAB classes for manipulating tensors: tensor, tensor as matrix,. Supply a positive definite correlation matrix, R , for estimating the spectral density . Using a matrix from the MATLAB Gallery collection as an example, this article discusses three variants of the QR algorithm available in MATLAB. There are a number of ways to compute the rank of a matrix. [4] describe and compare many algorithms for computing a matrix exponential. The multiplication between two 1000*1000 matrixes will take no more than 1 second in matlab. Please am finding it difficult to modify the code to enable the strassen algorithm applicable for odd dimensions. Function C = strassen(A, B, nmin) %STRASSEN Strassen's fast matrix multiplication algorithm. Sparse matrix algorithms lie in the intersection of graph theory and numerical 11 days to 7 minutes when my QR factorization method was added to MATLAB. The algorithm expm uses is described in [1] and [2]. Array indexing, concatenation, sorting, and reshaping. Try MATLAB, Simulink, and Other Products. This MATLAB function constructs an adaptive algorithm object based on the property that represents the inverse correlation matrix for the RLS algorithm. Tensor manipulations that can be used for fast algorithm prototyping. This function computes the fundamental matrix using the normalized eight-point algorithm [1] a fundamental matrix, f, by using the normalized 8-point algorithm.