Developer Reference for Intel® oneAPI Math Kernel Library for C
Mathematical Notation for LAPACK Routines
Descriptions of LAPACK routines use the following notation:
AH  |  
     For an M-by-N matrix A, denotes the conjugate transposed N-by-M matrix with elements: ![]() For a real-valued matrix, AH = AT.  |  
    
x·y  |  
     The dot product of two vectors, defined as: ![]()  |  
    
Ax = b  |  
     A system of linear equations with an n-by-n matrix A = {aij}, a right-hand side vector b = {bi}, and an unknown vector x = {xi}.  |  
    
AX = B  |  
     A set of systems with a common matrix A and multiple right-hand sides. The columns of B are individual right-hand sides, and the columns of X are the corresponding solutions.  |  
    
|x|  |  
     the vector with elements |xi| (absolute values of xi).  |  
    
|A|  |  
     the matrix with elements |aij| (absolute values of aij).  |  
    
||x||∞ = maxi|xi|  |  
     The infinity-norm of the vector x.  |  
    
||A||∞ = maxiΣj|aij|  |  
     The infinity-norm of the matrix A.  |  
    
||A||1 = maxjΣi|aij|  |  
     The one-norm of the matrix A. ||A||1 = ||AT||∞ = ||AH||∞  |  
    
||x||2  |  
     The 2-norm of the vector x: ||x||2 = (Σi|xi|2)1/2 = ||x||E (see the definition for Euclidean norm in this topic).  |  
    
||A||2  |  
     The 2-norm (or spectral norm) of the matrix A. ![]()  |  
    
||A||E  |  
     The Euclidean norm of the matrix A: ||A||E2 = ΣiΣj|aij|2.  |  
    
κ(A) = ||A||·||A-1||  |  
     The condition number of the matrix A.  |  
    
λi  |  
     Eigenvalues of the matrix A (for the definition of eigenvalues, see Eigenvalue Problems).  |  
    
σi  |  
     Singular values of the matrix A. They are equal to square roots of the eigenvalues of AHA. (For more information, see Singular Value Decomposition).  |  
    


