Approximations for optimal Laplace transform inversion

A function (p) of the Laplace transform operatorp is approximated by a finite linear combination of functions (p+ _r ), where (p) is a specific function ofp having a known analytic inverse (t), and is chosen in accordance with various considerations. Then parameters _r ,r=1, 2,...,n, and then corresponding coefficientsA _r of the (p + _r ) are determined by a least-square procedure. Then, the corresponding approximation to the inversef(t) of (p) is given by analytic inversion of _r=1 ⁿ A _r (p+ _r ). The method represents a generalization of a method of best rational function approximation due to the author [which corresponds to the particular choice (t)1], but is capable of yielding considerably greater accuracy for givenn.The computations for this paper were carried out on the CDC-6600 computer at the Computation Center of Tel-Aviv University. The author is grateful to Dr. H. Jarosch of the Weizmann Institute of Science Computer Center for use of their Powell minimization subroutine (Ref. 1).     

A comparative approach to Laplace transform inversion

A complex Laplace transform function was inverted by three numerical methods and compared to the small time and large time approximation curves. This technique enabled the best choice of an inversion method to be made, since one method gave excellent results, at both small and large times and moved smoothly from one curve to the other.     

Rational inversion of the Laplace transform

This paper studies new inversion methods for the Laplace transform of vector-valued functions arising from a combination of A-stable rational approximation schemes to the exponential and the shift operator semigroup. Each inversion method is provided in the form of a (finite) linear combination of the Laplace transform of the function and a finite amount of its derivatives. Seven explicit methods arising from A-stable schemes are provided, such as the Backward Euler, RadauIIA, Crank-Nicolson, and Calahan scheme. The main result shows that, if a function has an analytic extension to a sector containing the nonnegative real line, then the error estimate for each method is uniform in time.     

Special quadrature rules for Laplace transform inversion

Quadrature rules for Laplace transform inversion are studied that are adapted to the inversion of transforms corresponding to slowly varying long processes characteristic of linear viscoelasticity problems. The convergence of special quadrature rules for Laplace transform inversion is proved.     

On the inversion of the n-dimensional Laplace transform

In this paper we study the inversion of the multidimensionalLaplace transform by a combination of a general partial-fractionexpansion formula and the theory of residues. The ideas maybe applied to nonlinear systems defined by Volterra series.     

On the construction of quadrature rules for Laplace transform inversion

For Laplace transform inversion, a method for constructing quadrature rules of the highest degree of accuracy based on an asymptotic distribution of roots of special orthogonal polynomials on the complex plane is proposed.     

Numerical accuracy of real inversion formulas for the Laplace transform

In this article, we investigate and compare a number of real inversion formulas for the Laplace transform. The focus is on the accuracy and applicability of the formulas for numerical inversion. In this contribution, we study the performance of the formulas for measures concentrated on a positive half-line to continue with measures on an arbitrary half-line. As our trial measure concentrated on a positive half-line, we take the broad Gamma probability distribution family.     

On the inversion of the convolution and Laplace transform

We present a new inversion formula for the classical, finite, and asymptotic Laplace transform of continuous or generalized functions . The inversion is given as a limit of a sequence of finite linear combinations of exponential functions whose construction requires only the values of evaluated on a Müntz set of real numbers. The inversion sequence converges in the strongest possible sense. The limit is uniform if is continuous, it is in if , and converges in an appropriate norm or Fréchet topology for generalized functions . As a corollary we obtain a new constructive inversion procedure for the convolution transform ; i.e., for given and we construct a sequence of continuous functions such that .

     

New quadrature formulas for the numerical inversion of the Laplace transform

New quadrature formulas for the evaluation of the Bromwich integral, arising in the inversion of the Laplace transform are discussed. They are obtained by optimal addition of abscissas to Gaussian quadrature formulas. A table of abscissas and weights is given.     

Application of best rational function approximation for Laplace transform inversion

The application of a method of least squares Laplace transform inversion due to the author is discussed, and examples are given, which also serve to give us best trigonometric and exponential function approximations to some known functions. In particular the unit step function H(t-1) is considered, and the “best” approximations obtained for it would seem to have application in electrical network theory, including the design of delay lines.     

Least squares coefficients for a quadrature formula for Laplace transform inversion

A linear iterative method of least squares approximation of functions by exponentials due to Miller [9] is adapted to derive a set of least squares coefficients for an approximate Laplace transform inversion formula eq. (1). An earlier assumption made by Zakian [2] - that the approximation to the Laplace transform inverse will improve provided the approximation to the Dirac delta function is improved - is shown to be not substantiated for a number of test functions.     

Real inversion and jump formulae for the Laplace transform. Part I

Generalizations of the Laplace asymptotic method are obtained and real inversion formulae of the Post-Widder type for the Laplace transform are generalized. This paper is to be a part of the first author’s Ph.D. thesis written under the direction of the second author at The Hebrew University of Jerusalem. The participation of the second author in this paper has been sponsored in part by the Air Force Office of Scientific Research OAR through the European Office, Aerospace Research, United States Air Force.     

More on the weeks method for the numerical inversion of the Laplace transform

Summary Most of the numerical methods for the inversion of the Laplace Transform require the values of several incidental parameters. Generally, these parameters are related to the properties of the algorithm and to the analytical properties of the Laplace Transform functionF(s).One of the most promising inversion methods, the Weeks methods, computes the inverse functionf(t) as a series expansion of Laguerre functions involving two parameters, usually denoted by andb. In this paper we characterize the optimal choiceb _opt ofb, which maximizes the rate of convergence of the series, in terms of the location of the singularities ofF(s).     

Some exponentially decreasing error bounds for a numerical inversion of the Laplace transform

Convergence properties of a class of least-squares methods for finding approximate inverses of the Laplace transform are obtained by using reproducing kernel Hilbert space techniques (or, alternatively, related minimization techniques) and some classical interpolation results.     

A Hausdorff‐like moment problem and the inversion of the Laplace transform

We consider the problem of finding u ∈ L ²(I ), I = (0, 1), satisfying ∫_I u (x )x dx = μ _k , where k = 0, 1, 2, …, (α _k ) is a sequence of distinct real numbers greater than –1/2, and μ = (μ _kl ) is a given bounded sequence of real numbers. This is an ill‐posed problem. We shall regularize the problem by finite moments and then, apply the result to reconstruct a function on (0, +∞) from a sequence of values of its Laplace transforms. Error estimates are given. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Moment-recovered approximations of multivariate distributions: The Laplace transform inversion

The moment-recovered approximations of multivariate distributions are suggested. This method is natural in certain incomplete models where moments of the underlying distribution can be estimated from a sample of observed distribution. This approach is applicable in situations where other methods cannot be used, e.g. in situations where only moments of the target distribution are available. Some properties of the proposed constructions are derived. In particular, procedures of recovering two types of convolutions, the copula and copula density functions, as well as the conditional density function, are suggested. Finally, the approximation of the inverse Laplace transform is obtained. The performance of moment-recovered construction is illustrated via graphs of a simple density function.     

An efficient algorithm for regularization of Laplace transform inversion in real case

We address design of a numerical algorithm for solving the linear system arising in numerical inversion of Laplace transforms in real case [L. D’Amore, A. Murli, Regularization of a Fourier series method for the Laplace transform inversion with real data, Inverse Problems 18 (2002) 1185–1205]. The matrix has a condition number that grows almost exponentially and the singular values decay gradually towards zero. In such a case, because of this intrinsic strong instability, the main difficulty of any numerical computation is the ability of discovering at run time, only using data, what is the maximum attainable accuracy on the solution.

In this paper, we use GMRES with the aim of relating the current residuals to the maximum attainable accuracy of the approximate solution by using a suitable stopping rule. We prove that GMRES stops after, at most, as many iterations as the number of the largest eigenvalues (compared to the machine epsilon). We use a split preconditioner that symmetrically precondition the initial system. By this way, the largest eigenvalue dynamically provides the estimate of the condition number of the matrix.