CGSVD Compact generalized SVD of a matrix pair in regularization problems. sm = cgsvd(A,L) [U,sm,X,V] = cgsvd(A,L) , sm = [sigma,mu] Computes the generalized SVD of the matrix pair (A,L): [ A ] = [ U 0 ]*[ diag(sigma) 0 ]*inv(X) [ L ] [ 0 V ] [ 0 eye(n-p) ] [ diag(mu) 0 ] where U is m-by-n , sigma is p-by-1 V is p-by-p , mu is p-by-1 X is n-by-n . It is assumed that m >= n >= p, which is true in regularization problems. Reference: C. F. Van Loan, Computing the CS and the generalized singular value decomposition , Numer. Math. 46 (1985), 479-491. Per Christian Hansen, IMM, 12/19/97. Initialization.

cgsvd.m

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