Rational Approximation Algorithm Research Articles

An Algorithm for Real and Complex Rational Minimax Approximation

Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 6 August 2019Accepted: 08 July 2020Published online: 13 October 2020Keywordsrational approximation, barycentric formula, AAA algorithm, AAA-Lawson algorithm, iteratively reweighted least-squaresAMS Subject Headings41A20, 65D15Publication DataISSN (print): 1064-8275ISSN (online): 1095-7197Publisher: Society for Industrial and Applied MathematicsCODEN: sjoce3

Computing the 2-Adic Complexity of Two Classes Generalized Cyclotomic Sequences

This paper contributes to analyze the 2-adic complexity of a class of Ding-Helleseth generalized cyclotomic sequences and a class of Whiteman generalized cyclotomic sequences of periods of N = pq, wherep and q are two odd distinct primes with gcd(p - 1, q - 1) = 2 satisfyingp ≡ q ≡ 3 (mod 4). The results show that the 2-adic complexity of these sequences is at least pq - p - q - 1. Then it is large enough to resist the attacks of rational approximation algorithm.

The 2-Adic Complexity of Ding-Helleseth Generalized Cyclotomic Sequences of Order 2 and Period pq

This paper considers the 2-adic complexity of Ding-Helleseth generalized cyclotomic sequences of order 2 and period pq, where p and q are distinct odd primes with gcd(p - 1, q - 1) = 2, p - q - 3 (mod 4). These sequences have been proved to possess good linear complexity. Our results show that the 2-adic complexity of these sequences is at least pq - q - 1. Then it is large enough to resist the attack of the rational approximation algorithm.

A new algorithm on the minimal rational fraction representation of feedback with carry shift registers

In 1994, Klapper and Goresky (Proceedings of the 1993 Cambridge Security Workshop, Lecture Notes in Computer Science, vol 809, Cambridge, pp 174–178, 1994) proposed a new device called feedback with carry shift register to generate pseudo-random sequences instead of using the traditional device linear feedback shift register. They raised an algorithm called as rational approximation algorithm to recover the device for a given sequence (Klapper and Goresky, Advances in Cryptology, Crypto’95, Lecture Notes in Computer Science, vol 963, Springer, Berlin, pp 262–274, 1995). In this paper, we propose a new algorithm by introducing a new parameter and get the best rational approximation of the sequence much more quickly, especially when the size of the sequence increases dramatically. Unlike most of known algorithms, we can solve the minimal lattice basis instead of one shortest vector. Besides, we can prove that the solution of each step is optimal regardless of the length of the input sequence theoretically.

A unified view of some numerical methods for fractional diffusion

In recent years, a number of numerical methods for the solution of fractional Laplace and, more generally, fractional diffusion problems have been proposed. The approaches are quite diverse and include, among others, the use of best uniform rational approximations, quadrature for Dunford–Taylor-like integrals, finite element approaches for a localized elliptic extension into a space of increased dimensions, and time stepping methods for a parabolic reformulation of the fractional differential equation.A systematic comparison, both theoretical and experimental, of these approaches has thus far been lacking. A main contribution of the present work is the observation that all approaches mentioned above can, in fact, be interpreted as realizing different rational approximations of a univariate function over the spectrum of the original (non-fractional) diffusion operator. While this is obvious for some of the methods, it is a new result in particular for extension-based and time stepping approaches.This observation allows us to cast all described methods into a unified theoretical and computational framework, which has a number of benefits. Theoretically, it enables us to develop new convergence proofs for several of the studied methods, clarifies similarities and differences between the approaches, suggests how to design new and improved methods, and allows a direct comparison of the relative performance of the various methods. Practically, it provides a single, simple to implement, efficient and fully parallel algorithm for the realization of all studied methods; for instance, this immediately yields a fast and memory-efficient way of realizing all tensor product extension methods and lets us parallelize the otherwise inherently sequential time stepping approach.Finally, we present a detailed numerical study comparing all investigated methods for various fractional exponents and draw conclusions from the results. The comparison is made fair by the central insight that the computational effort of all these methods depends only on a single parameter, the degree of the underlying rational approximation. As a point of comparison, we also test a simple rational approximation method based on a black-box direct rational approximation algorithm which performs very well in practice.

Bounds for variable degree rational L∞ approximations to the matrix exponential

In this work we derive new alternatives for efficient computation of the matrix exponential which is useful when solving Linear Initial Value Problems, vibratory systems or after semidiscretization of PDEs. We focus especially on the two classes of normal and nonnegative matrices and we present intervals of applications for rational L∞ approximations of various degrees for these types of matrices in the lines of [7, 8]. Our method relies on Remez algorithm for rational approximation while the innovation here is the choice of the starting set of non-symmetrical Chebyshev points. Only one Remez iteration is then usually enough to quickly approach the actual L∞ approximant.

A lower bound on the 2-adic complexity of the modified Jacobi sequence

Let $p,q$ be distinct primes satisfying $\mathrm{gcd}(p-1,q-1)=d$ and let $D_i$, $i=0,1,\cdots,d-1$, be Whiteman's generalized cyclotomic classes with $Z_{pq}^{\ast}=\cup_{i=0}^{d-1}D_i$. In this paper, we give the values of Gauss periods based on the generalized cyclotomic sets $D_0^{\ast}=\sum_{i=0}^{\frac{d}{2}-1}D_{2i}$ and $D_1^{\ast}=\sum_{i=0}^{\frac{d}{2}-1}D_{2i+1}$. As an application, we determine a lower bound on the 2-adic complexity of modified Jacobi sequence. Our result shows that the 2-adic complexity of modified Jacobi sequence is at least $pq-p-q-1$ with period $N=pq$. This indicates that the 2-adic complexity of modified Jacobi sequence is large enough to resist the attack of the rational approximation algorithm (RAA) for feedback with carry shift registers (FCSRs).

The AAA Algorithm for Rational Approximation

We introduce a new algorithm for approximation by rational functions on a real or complex set of points, implementable in 40 lines of Matlab and requiring no user input parameters. Even on a disk or interval the algorithm may outperform existing methods, and on more complicated domains it is especially competitive. The core ideas are (1) representation of the rational approximant in barycentric form with interpolation at certain support points and (2) greedy selection of the support points to avoid exponential instabilities. The name AAA stands for "adaptive Antoulas--Anderson" in honor of the authors who introduced a scheme based on (1). We present the core algorithm with a Matlab code and nine applications and describe variants targeted at problems of different kinds. Comparisons are made with vector fitting, RKFIT, and other existing methods for rational approximation.

The exact autocorrelation distribution and 2-adic complexity of a class of binary sequences with almost optimal autocorrelation

Pseudo-random sequences with good statistical properties, such as low autocorrelation, high linear complexity and large 2-adic complexity, have been used in designing reliable stream ciphers. In this paper, we obtain the exact autocorrelation distribution of a class of binary sequences with three-level autocorrelation and analyze the 2-adic complexity of this class of sequences. Our results show that the 2-adic complexity of such a binary sequence with period N is at least (N + 1) − log2 (N + 1). We further show that it is maximal for infinitely many cases. This indicates that the 2-adic complexity of this class of sequences is large enough to resist the attack of the rational approximation algorithm (RAA) for feedback with carry shift registers (FCSRs).

The RKFIT Algorithm for Nonlinear Rational Approximation

The RKFIT algorithm outlined in [M. Berljafa and S. Guettel, Generalized rational Krylov decompositions with an application to rational approximation, SIAM J. Matrix Anal. Appl., 2015] is a Krylov-based approach for solving nonlinear rational least squares problems. This paper puts RKFIT into a general framework, allowing for its extension to nondiagonal rational approximants and a family of approximants sharing a common denominator. Furthermore, we derive a strategy for the degree reduction of the approximants, as well as methods for their conversion to partial fraction form, for the efficient evaluation, and root-finding. We also discuss commons and differences of RKFIT and the popular vector fitting algorithm. A MATLAB implementation of RKFIT is provided and numerical experiments, including the fitting of a MIMO dynamical system and an optimization problem related to exponential integration, demonstrate its applicability.

AFSRs synthesis with the extended Euclidean rational approximation algorithm

Pseudo-random sequence generators are widely used in many areas, such as stream ciphers, radar systems, Monte-Carlo simulations and multiple access systems. Generalization of linear feedback shift registers (LFSRs) and feedback with carry shift registers (FCSRs), algebraic feedback shift registers (AFSRs) [ 7 ] can generate pseudo-random sequences over an arbitrary finite field. In this paper, we present an algorithm derived from the Extended Euclidean Algorithm that can efficiently find a smallest AFSR over a quadratic field for a given sequence. It is an analog of the Extended Euclidean Rational Approximation Algorithm [ 1 ] used in solving the FCSR synthesis problem. For a given sequence $\mathbf{a}$, $2\Lambda(\alpha)+1$ terms of sequence $\mathbf{a}$ are needed to find the smallest AFSR, where $\Lambda(\alpha)$ is a complexity measure that reflects the size of the smallest AFSR that outputs $\mathbf{a}$.

Best two‐parameter rational approximation algorithm of given order: a variation of adaptive Fourier decomposition

The concept of mono‐component is widely used in nonstationary signal processing and time‐frequency analysis. In this paper, we construct several classes of complete rational function systems in the Hardy space, whose boundary values are mono‐components. Then, we propose a best approximation algorithm (BAA) based on optimal selections of two parameters in the orthonormal bases according to the approximation error. Effectiveness of BAA is evaluated by comparison experiments with the classical Fourier decomposition algorithm. It is also shown that BAA has promising results for filtering out noises and dealing with real‐world signals. Copyright © 2014 John Wiley & Sons, Ltd.

Bounds for variable degree rational [formula omitted] approximations to the matrix cosine

In this work we derive new alternatives for efficient computation of the matrix cosine which is useful when solving second order Initial Value Problems such as free vibration. We focus especially on the two classes of normal and nonnegative matrices and we present intervals of applications for rational L∞ approximations of various degrees for these types of matrices in the lines of Hargreaves and Higham (2005). Our method relies on Remez algorithm for rational approximation while the innovation here is the choice of the starting set of non-symmetrical Chebyshev points. Only one Remez iteration is then usually enough to quickly approach the actual L∞ approximant.

Double precision rational approximation algorithm for the inverse standard normal second order loss function

We present a double precision algorithm based upon rational approximations for the inverse standard normal second order loss function. This function is used frequently in inventory management. No direct approximation or closed formulation exists for the inverse standard normal second order loss function. Calculations are currently based on root-finding methods and intermediate computations of the cumulative normal distribution or tabulations. Results then depend on the accuracy and valid range of that underlying function. We deal with these issues and present a direct, double precision accurate algorithm valid in the full range of double precision floating point numbers.

A method for the integer-order approximation of fractional-order systems

A procedure for approximating fractional-order systems by means of integer-order state-space models is presented. It is based on the rational approximation of fractional-order operators suggested by Oustaloup. First, a matrix differential equation is obtained from the original fractional-order representation. Then, this equation is realized in a state-space form that has a sparse block-companion structure. The dimension of the resulting integer-order model can be reduced using an efficient algorithm for rational L2 approximation. Two numerical examples are worked out to show the performance of the suggested technique.

Double precision rational approximation algorithm for the inverse standard normal first order loss function

We present a double precision algorithm based upon rational approximations for the inverse standard normal first order loss function. This function is used frequently in inventory management. No direct approximation or closed formulation exists for the inverse standard normal first order loss function. Calculations are currently based on root-finding methods and intermediate computations of the cumulative normal distribution or tabulations. Results then depend on the accuracy and valid range of that underlying function. We deal with these issues and present a direct, double precision accurate algorithm valid in the full range of double precision floating point numbers.

Approximating rational triangular Bézier surfaces by polynomial triangular Bézier surfaces

An attractive method for approximating rational triangular Bézier surfaces by polynomial triangular Bézier surfaces is introduced. The main result is that the arbitrary given order derived vectors of a polynomial triangular surface converge uniformly to those of the approximated rational triangular Bézier surface as the elevated degree tends to infinity. The polynomial triangular surface is constructed as follows. Firstly, we elevate the degree of the approximated rational triangular Bézier surface, then a polynomial triangular Bézier surface is produced, which has the same order and new control points of the degree-elevated rational surface. The approximation method has theoretical significance and application value: it solves two shortcomings-fussy expression and uninsured convergence of the approximation-of Hybrid algorithms for rational polynomial curves and surfaces approximation.

Rational offset approximation of rational Bézier curves

The problem of parametric speed approximation of a rational curve is raised in this paper. Offset curves are widely used in various applications. As for the reason that in most cases the offset curves do not preserve the same polynomial or rational polynomial representations, it arouses difficulty in applications. Thus approximation methods have been introduced to solve this problem. In this paper, it has been pointed out that the crux of offset curve approximation lies in the approximation of parametric speed. Based on the Jacobi polynomial approximation theory with endpoints interpolation, an algebraic rational approximation algorithm of offset curve, which preserves the direction of normal, is presented.

A Novel algorithm on network reliability estimation

We propose a rational approximation algorithm for network reliability estimation in this paper. Our algorithm can be applied to estimate both the all-terminal reliability measure and the reliability of networks with various protection algorithms. Our algorithm is very efficient and it can obtain the whole reliability function curve.

The Newton differential correction algorithm for rational Chebyshev approximation with constrained denominators

An algorithm for constrained rational Chebyshev approximation is introduced that combines the idea of an algorithm due to Hettich and Zencke, for which superlinear convergence is guaranteed, with the auxiliary problem used in the well-known original differential correction method. Superlinear convergence of the algorithm is proved. Numerical examples illustrate the fast convergence of the method and its advantages compared with the algorithm of Hettich and Zencke.