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Matrix Hessenberg

The determination of eigenvalues and eigenvectors of the matrix A is based on a routine by Grad and Brebner (1968). The matrix is first scaled by a sequence of similarity transformations and then normalized to have the Euclidian norm equal to one. The matrix is reduced to an upper Hessenberg form by Householder s method. Then the QR double-step iterative process is performed on the Hessenberg matrix to compute the eigenvalues. The eigenvectors are obtained by inverse iteration. [Pg.174]

These zeros uk of QK(u) coincide with the eigenvalues of both the evolution matrix U and the corresponding Hessenberg matrix H from Eqs. (131) and (130), respectively. The zeros of Qk(u) are called eigenzeros. The structure of CM is determined by its scalar product for analytic functions of complex variable z or u. For any two regular functions/(m) and g(u) from CM, the scalar product in CM is defined by the generalized Stieltjes integral ... [Pg.183]

Note also that for a generic linear generator A such as that of CODDE (Sec. 2.3), the Lanczos or Arnoldi algorithm results in an upper Hessenberg matrix such that [45, 46, 52]... [Pg.32]

A supertriangular matrix, also called a Hessenberg matrix, is one that ha.s all zero elements below die subdiagonal, such as the upper Hessenberg matrix of Eq. (2.57) ... [Pg.76]

The complete elementary similarity transformation that converts matrix A to the upper Hessenberg matrix H is shown by... [Pg.127]

The elementary similarity transformation to produce an upper Hessenberg matrix in formula form is as follows ... [Pg.128]

The QR algorithm, which will be discussed next, utilizes the upper Hessenberg matrix H to determine its eigenvalues, which are equivalent to the eigenvalues of matrix A. [Pg.128]

Repeat steps 4 and 5, calculating the transformation matrix and eliminating one element on subdiagonal in each set of steps. The application of steps 4 and 5 for (n - 1) times, with the counter q increasing from 1 to ( -1) and the counter p set at q + 1), will convert the Hessenberg matrix //, to a triangular matrix Ry... [Pg.133]

Use as the new Hessenberg matrix and repeat steps 2-8 until < e, where e... [Pg.133]

The method of Hessenberg, which reduces the matrix to Hessenberg form, replaces the matrix A by... [Pg.75]

A Hessenberg form H (the same form but not the same matrix) can also be obtained by a sequence of orthogonal transformations, either by plane rotations (the method of Givens), each rotation annihilating an individual element, or by using unitary hermitians, I — 2wiwf, wfwt = 1 (the method of Householder), each of which annihilates ill possible elements in a column. Thus, at the first step, if A = A, and... [Pg.75]

It may be shown that the DAE system corresponding to the discrete form of the compressible stagnation-flow equations is of the so-called Hessenberg-index-two structure [46], which is represented by Eq. 17.29. The constraints g do not depend on x, and the matrix... [Pg.717]

The matrix elements /i, y of the upper Hessenberg representation of L are thus automatically generated during the construction of the vectors vy. The essence of the short-iterative-Arnoldi propagator is to form an explicit representation of the exponential operator in the n-dimen-sional Krylov space based on the initial density matrix, cr t). [Pg.96]

Since Avj span(Vj+i), and v,- G spanCVj+i) only if z < j +1, A hsis the important property that Aij = 0 for z > j +1. This kind of matrix, known as upper-Hessenberg, is usually much easier to manipulate than A because A is almost upper triangular. Thus, the philosophy behind the Krylov space based methods (KSM) is to transform the original linear system into the simpler form Ax = b where x = V x and b = Vjb, which can be solved more easily. The computational effort is usually dominated by the construction and orthogonalization of the transformation matrix Vp, which requires a matrix vector multiply at each iteration. [Pg.94]

In the determination of eigenvalues, it is desirable to reduce matrix A to a super-triangular matrix of upper Hessenberg form ... [Pg.126]

Estimation of the shift factor Yj is relatively easy when the matrix has been reduced to upper Hessenberg form ... [Pg.132]


See other pages where Matrix Hessenberg is mentioned: [Pg.172]    [Pg.182]    [Pg.33]    [Pg.77]    [Pg.133]    [Pg.172]    [Pg.182]    [Pg.33]    [Pg.77]    [Pg.133]    [Pg.73]    [Pg.76]    [Pg.77]    [Pg.78]    [Pg.323]    [Pg.294]    [Pg.145]    [Pg.182]    [Pg.96]    [Pg.97]    [Pg.123]    [Pg.123]    [Pg.131]   
See also in sourсe #XX -- [ Pg.174 ]




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