Lanczos approximation
Pythagoras0 (토론 | 기여)님의 2021년 2월 17일 (수) 00:48 판
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- ID : Q6483801
말뭉치
- The Lanczos approximation is a particularly effective method for computing values of the Gamma function to high precision.[1]
- To facilitate an elegant C++ implementation of the Lanczos approximation, I have written a partial C++ wrapper for the floating point functions of GMP.[1]
- The Lanczos approximation has fewer of these problems, provided that the coefficients are computed accurately enough.[2]
- The Lanczos Approximation as implemented in the Boost C++ Libraries.[2]
- We report that for fixed real parts of the free parameter that using complex coefficients both increases the computational cost of the Lanczos approximation while drecreasing the accuracy...[3]
- In mathematics, the Lanczos approximation is a method for computing the Gamma function numerically, published by Cornelius Lanczos in 1964.[4]
- For a well-chosen constant g and a small number of terms in the series, the Lanczos approximation is accurate to within floating-point precision.[5]
- In mathematics, the Lanczos approximation is a method for computing the gamma function numerically, published by Cornelius Lanczos in 1964.[6]
- Among others, the Padé-via-Lanczos approximation provides an efficient solution.[7]
- The Lanczos approximation is used to calculate Gamma function numerically.[8]
- The Lanczos approximation is a method for computing the Gamma function numerically, published by Cornelius Lanczos in 1964.[8]
- Using Lanczos Approximation.[9]
- In this paper, we use the idea of thick-restart and adaptive preconditioning for solving linear systems to improve convergence of the Lanczos approximation.[10]
- 𝑣 ℓ + 1 for the Lanczos approximation, so that the vectors 𝑟 ℓ ≡ 𝑟 ℓ ( 0 ) and 𝑟 ℓ ( 𝑡 ) are aligned; however their magnitudes are different.[10]
- It is also worth pointing out that the Lanczos approximation for this preconditioned matrix function reduces much more rapidly than for the case where preconditioning (dotted line) is not used.[10]
- The Lanczos approximation in this example again lies almost entirely on the curve that represents the optimal approximation obtainable from the Krylov subspace.[10]
소스
- ↑ 1.0 1.1 The Lanczos approximation of the Gamma function
- ↑ 2.0 2.1 Coefficients for the Lanczos Approximation to the Gamma Function at MROB
- ↑ The Lanczos Approximation for the $\Gamma$-Function with Complex Coefficients
- ↑ JavaScript Math: Calculate Lanczos approximation gamma
- ↑ jcboyd/study-no-1: An implementation of the Lanczos approximation in C with Python wrapper
- ↑ Lanczos approximation
- ↑ EFFICIENT SOUND POWER COMPUTATION OF OPEN STRUCTURES WITH INFINITE/FINITE ELEMENTS AND BY MEANS OF THE PADÉ-VIA-LANCZOS ALGORITHM
- ↑ 8.0 8.1 Online calculator: Gamma function
- ↑ (PDF) Julia and Mandelbrot Sets of the Gamma Function Using Lanczos Approximation
- ↑ 10.0 10.1 10.2 10.3 A Numerical Solution Using an Adaptively Preconditioned Lanczos Method for a Class of Linear Systems Related with the Fractional Poisson Equation
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위키데이터
- ID : Q6483801
Spacy 패턴 목록
- [{'LOWER': 'lanczos'}, {'LEMMA': 'approximation'}]