1998
DOI: 10.1016/s0377-0427(98)00084-3
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On an integrable discretization of the Rayleigh quotient gradient system and the power method with a shift

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Cited by 9 publications
(8 citation statements)
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“…Simultaneously, the first column of Q converges to a normalized eigenvector of the maximal eigenvalue µ 1 of the symmetric matrix N . It is shown in [32] that by discretizing the Rayleigh quotient gradient system a recurrence relation of the power method with shift, for computing largest eigenvalue and its eigenvector, is derived. The optimal shift is then found by using an explicit solution.…”
Section: Integrable Gradient Flows Of Brockett Formmentioning
confidence: 99%
See 1 more Smart Citation
“…Simultaneously, the first column of Q converges to a normalized eigenvector of the maximal eigenvalue µ 1 of the symmetric matrix N . It is shown in [32] that by discretizing the Rayleigh quotient gradient system a recurrence relation of the power method with shift, for computing largest eigenvalue and its eigenvector, is derived. The optimal shift is then found by using an explicit solution.…”
Section: Integrable Gradient Flows Of Brockett Formmentioning
confidence: 99%
“…Such discretization has explicit solutions, conserved quantities and some other integrable features and is sometimes called an "integrable discretization" [30]. Indeed in [32] we see that an integrable discretization of the Rayleigh quotient gradient system gives rise to a recurrence relation of the power method with shift. The basic idea is as follows.…”
Section: Discretizations Of Integrable Systems To Design Numerical Almentioning
confidence: 99%
“…(For a more sophisticated discretization in the unpreconditioned Hermitian case, along with a cautionary note about use of large step-size in the forward Euler method, see [28]. )…”
Section: Discrete Dynamical Systemsmentioning
confidence: 99%
“…Simple discretizations, such as Euler's method (1.1), do not typically respect such invariants, giving approximate solutions that drift from the manifold. Invariant-preserving alternatives (see, e.g., [18,26]) generally require significantly more computation per step (though a tractable method for the unpreconditioned, Hermitian case has been proposed by Nakamura, Kajiwara, and Shiotani [28]). Our goal is to explain the relationship between convergence and stability of the continuous and discrete dynamical systems.…”
mentioning
confidence: 99%
“…The third example is the power method (cf [23]) for finding maximal eigenvalue of symmetric matrices. The power method with a shift of origin is shown to be an integrable discretization of the Rayleigh quotient gradient system [17], where no such tau function appears.…”
Section: Introductionmentioning
confidence: 99%