% SVD (sigular value decomposition,SVD) is another kind of orthogonal decomposition method of matrix; SVD decomposition method is the most reliable,% it spend nearly 10 times than the QR Decomposition method of calculation time. [U,S,V]=svvd (a), where u and v represent two mutually orthogonal matrices,% s represents a pair of point matrix. With the QR Decomposition method of the same, the original matrix a does not have to square matrices. % Using the SVD decomposition is the use of minimum squared error methods and data compression solutions. With SVD decomposition method for solving linear equations




File list:
SVD.c