Subtraction-free recurrence relations for lower bounds of the minimal singular value of an upper bidiagonal matrix

نویسندگان

  • Takumi Yamashita
  • Kinji Kimura
  • Yoshimasa Nakamura
چکیده

On an N × N upper bidiagonal matrix B, where all the diagonals and the upper subdiagonals are positive, and its transpose BT , it is shown in the recent paper [4] that quantities JM(B) ≡ Tr(((BT B)M)−1) (M = 1, 2, . . . ) gives a sequence of lower bounds θM(B) of the minimal singular value of B through θM(B) ≡ (JM(B)). In [4], simple recurrence relations for computing all the diagonals of ((BT B)M)−1 and ((BBT )M)−1 are also presented. The square of θM(B) can be used as a shift of origin in numerical algorithms for computing all the singular values of B. In this paper, new recurrence relations which have advantages to the old ones in [4] are presented. The new recurrence relations consist of only addition, multiplication and division among positive quantities. Namely, they are subtraction-free. This property excludes any possibility of cancellation error in numerical computation of the traces JM(B). Computational cost for the trace JM(B) (M = 1, 2, . . . ) and efficient implementations for J2(B) and J3(B) are also discussed.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Conserved quantities of the discrete finite Toda equation and lower bounds of the minimal singular value of upper bidiagonal matrices

Some numerical algorithms are known to be related to discrete-time integrable systems, where it is essential that quantities to be computed (for example, eigenvalues and singular values of a matrix, poles of a continued fraction) are conserved quantities. In this paper, a new application of conserved quantities of integrable systems to numerical algorithms is presented. For an N × N (N ≥ 2) rea...

متن کامل

A QR-method for computing the singular values via semiseparable matrices

A QR–method for computing the singular values via semiseparable matrices. Abstract The standard procedure to compute the singular value decomposition of a dense matrix, first reduces it into a bidiagonal one by means of orthogonal transformations. Once the bidiagonal matrix has been computed, the QR–method is applied to reduce the latter matrix into a diagonal one. In this paper we propose a ne...

متن کامل

More Accurate Bidiagonal Reduction for Computing the Singular Value Decomposition

Bidiagonal reduction is the preliminary stage for the fastest stable algorithms for computing the singular value decomposition. However, the best error bounds on bidiagonal reduction methods are of the form A + A = UBV T ; kAk 2 " M f(n)kAk 2 where B is bidiagonal, U and V are orthogonal, " M is machine precision, and f(n) is a modestly growing function of the dimensions of A. A Givens-based bi...

متن کامل

Bidiagonalization as a fundamental decomposition of data in linear approximation problems

• First, the lower bidiagonal matrix A11 with nonzero bidiagonal elements has full column rank and its singular values are simple. Consequently, any zero singular values or repeats that A has must appear in A22. • Second, A11 has minimal dimensions, and A22 has maximal dimensions, over all orthogonal transformations giving the block structure in (2), without any additional assumptions on the st...

متن کامل

Admissibility analysis for discrete-time singular systems with time-varying delays by adopting the state-space Takagi-Sugeno fuzzy model

This paper is pertained with the problem of admissibility analysis of uncertain discrete-time nonlinear singular systems by adopting the state-space Takagi-Sugeno fuzzy model with time-delays and norm-bounded parameter uncertainties. Lyapunov Krasovskii functionals are constructed to obtain delay-dependent stability condition in terms of linear matrix inequalities, which is dependent on the low...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011