Much of MATLAB's power comes from its matrix functions. The most useful
eig eigenvalues and eigenvectors chol cholesky factorization svd singular value decomposition inv inverse lu LU factorization qr QR factorization hess hessenberg form schur schur decomposition rref reduced row echelon form expm matrix exponential sqrtm matrix square root poly characteristic polynomial det determinant size size norm 1-norm, 2-norm, F-norm, infinity-norm cond condition number in the 2-norm rank rank
MATLAB functions may have single or multiple output arguments. For example,
y = eig(A), or simply eig(A)produces a column vector containing the eigenvalues of A while
[U,D] = eig(A)produces a matrix U whose columns are the eigenvectors of A and a diagonal matrix D with the eigenvalues of A on its diagonal. Try it!