B = cumsum(A) B = 1 2 3 4 5 6 7 8 2 4 6 8 10 12 14 16 3 6 9 12 15 18 21 24 4 8 12 16 20 24 28 32 5 10 15 20 25 30 35 40 6 12 18 24 30 36 42 48 7 14 21 28 35 42 49 56 8 16 24 32 40 48 56 64 9 18 27 36 45 54 63 72 10 20 30 40 50 60 70 80 11 22 33 44 55 66 77 88 12 24 36 48 60 72 84 96 A A = 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 B = (cumsum(A'))' B = 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 1 3 6 10 15 21 28 36 C = cumsum(B) C = 1 3 6 10 15 21 28 36 2 6 12 20 30 42 56 72 3 9 18 30 45 63 84 108 4 12 24 40 60 84 112 144 5 15 30 50 75 105 140 180 6 18 36 60 90 126 168 216 7 21 42 70 105 147 196 252 8 24 48 80 120 168 224 288 9 27 54 90 135 189 252 324 10 30 60 100 150 210 280 360 11 33 66 110 165 231 308 396 12 36 72 120 180 252 336 432 A A = 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 help eig EIG Eigenvalues and eigenvectors. E = EIG(X) is a vector containing the eigenvalues of a square matrix X. [V,D] = EIG(X) produces a diagonal matrix D of eigenvalues and a full matrix V whose columns are the corresponding eigenvectors so that X*V = V*D. [V,D] = EIG(X,'nobalance') performs the computation with balancing disabled, which sometimes gives more accurate results for certain problems with unusual scaling. If X is symmetric, EIG(X,'nobalance') is ignored since X is already balanced. E = EIG(A,B) is a vector containing the generalized eigenvalues of square matrices A and B. [V,D] = EIG(A,B) produces a diagonal matrix D of generalized eigenvalues and a full matrix V whose columns are the corresponding eigenvectors so that A*V = B*V*D. EIG(A,B,'chol') is the same as EIG(A,B) for symmetric A and symmetric positive definite B. It computes the generalized eigenvalues of A and B using the Cholesky factorization of B. EIG(A,B,'qz') ignores the symmetry of A and B and uses the QZ algorithm. In general, the two algorithms return the same result, however using the QZ algorithm may be more stable for certain problems. The flag is ignored when A and B are not symmetric. See also condeig, eigs, ordeig. Overloaded methods: lti/eig sym/eig Reference page in Help browser doc eig eig(C) ??? Error using ==> eig Matrix must be square. eig(C'*C) ans = 1.0e+06 * -0.0000 -0.0000 -0.0000 -0.0000 0.0000 0.0000 0.0000 1.8798 svd(C) ans = 1.0e+03 * 1.3711 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 diary