Truncation approximants to probabilistic evolution of ordinary differential equations under initial conditions via bidiagonal evolution matrices: simple case

In this work, we investigate the probabilistic evolution approach (PEA) to ordinary differential equations whose evolution matrices are composed of only two diagonals under certain initial value impositions. We have been able to develop analytic expressions for truncation approximants which can be generated by using finite left uppermost square blocks in the denumerable infinite number of PEA equations and their infinite limits. What we have revealed is the fact that the truncation approximants converge for initial value parameter, values residing at most in a disk centered at the expansion point and excluding the nearest zero(es). The numerical implementations validate this formation.     

Adaptive triangular-mesh reconstruction by mean-curvature-based refinement from point clouds using a moving parabolic approximation

We use a moving parabolic approximation (MPA) to reconstruct a triangular mesh that approximates the underlying surface of a point cloud from closed objects. First, an efficient strategy is presented for constructing a hierarchical grid with adaptive resolution and generating an initial mesh from point clouds. By implementing the MPA algorithm, we can estimate the differential quantities of the underlying surface, and subsequently, we can obtain the local quadratic approximants of the squared distance function for any point in the vicinity of the target shape. Thus, second, we adapt the mesh to the target shape by an optimization procedure that minimizes a quadratic function at each step. With the objective of determining the geometrical features of the target surface, we refine the approximating mesh selectively for the non-flat regions by comparing the estimated curvature from the point clouds and the estimated curvatures computed from the current mesh. Finally, we present various examples that demonstrate the robustness of our method and show that the resulting reconstructions preserve geometric details.     

Solution of general Padé fitting problem via continued-fraction expansion

A computational algorithm is presented to expand a given function into the multipoint continued fractions from its power series expansions about arbitrary points, including the point at infinity. The convergents of the multipoiat continued fractions form a class of multipoint Padé approximants. An example is provided to illustrate the algorithm.     

Generalized Homogeneous Multivariate Matrix PadÉ-Type Approximants and PadÉ Approximants

Generalized homogeneous multivariate matrix Pade-type approximants (GHMPTA) and Pade approximants are studied in ways similar to those of Brezinski and Kida in the scalar cases. By choosing an arbitrary monic bivariate scalar polynomial from the triangular form as the generating one of the approximant, we discuss their several typical important properties and study the connection between generalized homogeneous bivariate matrix Pade-type approximants and Pade approximants. The arguments given in detail in two variables can be extended directly to the case of d variables (d ges 2).     

Approximation of trajectories of non-linear systems by iterates of systems with linear state dynamics

A modification of an iterative Picard process is proposed to approximate the output of a non-linear system by a concatenation of systems with linear state dynamics and non-linear outputs. A local uniform convergence result is given. The motivating example is a non-linear system that arises in surface plasmon resonance experiments to determine protein–protein interaction constants. We show with simulations that for this example the approximants converge not only locally but over the full time interval of interest in the application.     

Efficient surface reconstruction using generalized coulomb potentials

We propose a novel, geometrically adaptive method for surface reconstruction from noisy and sparse point clouds, without orientation information. The method employs a fast convection algorithm to attract the evolving surface towards the data points. The force field in which the surface is convected is based on generalized Coulomb potentials evaluated on an adaptive grid (i.e., an octree) using a fast, hierarchical algorithm. Formulating reconstruction as a convection problem in a velocity field generated by Coulomb potentials offers a number of advantages. Unlike methods which compute the distance from the data set to the implicit surface, which are sensitive to noise due to the very reliance on the distance transform, our method is highly resilient to shot noise since global, generalized Coulomb potentials can be used to disregard the presence of outliers due to noise. Coulomb potentials represent long-range interactions that consider all data points at once, and thus they convey global information which is crucial in the fitting process. Both the spatial and temporal complexities of our spatially-adaptive method are proportional to the size of the reconstructed object, which makes our method compare favorably with respect to previous approaches in terms of speed and flexibility. Experiments with sparse as well as noisy data sets show that the method is capable of delivering crisp and detailed yet smooth surfaces.     

Routh approximations for reducing order of linear, time-invariant systems

A new method of approximating the transfer function of a high-order linear system by one of lower order is proposed. Called the "Routh approximation method" because it is based on an expansion that uses the Routh table of the original transfer function, the method has a number of useful properties: if the original transfer function is stable, then all approximants are stable; the sequence of approximants converge monotonically to the original in terms of "impulse response" energy; the approximants are partial Padé approximants in the sense that the firstkcoefficients of the power series expansions of thekth-order approximant and of the original are equal; the poles and zeros of the approximants move toward the poles and zeros of the original as the order of the approximation is increased. A numerical example is given for the calculation of the Routh approximants of a fourth-order transfer function and for illustration of some of the properties.     

Recursive formulation of the matrix Padé approximation in packed storage

The Extended Euclidean algorithm for matrix Padé approximants is applied to compute matrix Padé approximants when the coefficient matrices of the input matrix polynomial are triangular. The procedure given by Bjarne S. Anderson et al. for packing a triangular matrix in recursive packed storage is applied to pack a sequence of lower triangular matrices of a matrix polynomial in recursive packed storage. This recursive packed storage for a matrix polynomial is applied to compute matrix Padé approximants of the matrix polynomial using the Matrix Padé Extended Euclidean algorithm in packed form. The CPU time and memory comparison, in computing the matrix Padé approximants of a matrix polynomial, between the packed case and the non-packed case are described in detail.     

Methods to reduce non-linear mechanical systems for instability computation

Summary Non-linear dynamical structures depending on control parameters are encountered in many areas of science and engineering. In the study of non-linear dynamical systems depending on a given control parameter, the stability analysis and the associated non-linear behaviour in a near-critical steady-state equilibrium point are two of the most important points; they make it possible to validate and characterize the non-linear structures. Stability is investigated by determining eigenvalues of the linearized perturbation equations about each steady-state operating point, or by calculating the Jacobian of the system at the equilibrium points. While the conditions and the values of the parameters which cause instability can be investigated by using linearized equations of motion studies of the non-linear behaviour of vibration problems, on the other hand, require the complete non-linear expressions of systems. Due to the complexity of non-linear systems and to save time, simplifications and reductions in the mathematical complexity of the non-linear equations are usually required. The principal idea for these non-linear methods is to reduce the order of the system and eliminate as many non-linearities as possible in the system of equations. In this paper, a study devoted to evaluating the instability phenomena in non-linear models is presented. It outlines stability analysis and gives a non-linear strategy by constructing a reduced order model and simplifying the non-linearities, based on three non-linear methods: the centre manifold concept, the rational approximants and the Alternating Frequency/Time domain method. The computational procedures to determine the reduced and simplified system via the centre manifold approach and the fractional approximants, as well as the approximation of the responses as a Fourier series via the harmonic balance method, are presented and discussed. These non-linear methods for calculating the dynamical behaviour of non-linear systems with several degrees-of-freedom and non-linearities are tested in the case of mechanical systems with many degrees-of-freedom possessing polynomial non-linearities. Results obtained are compared with those estimated by a classical Runge-Kutta integration procedure. Moreover, an extension of the centre manifold approach using rational approximants is proposed and used to explore the dynamics of non-linear systems, by extending the domain of convergence of the non-linear reduced system and evaluating its performance and suitability.     

Construction of the characteristic polynomial of a matrix

A connection between Padé approximants and characteristic polynomial of a matrix with complex, in general, elements is established. A system of homogeneous, first-order ordinary differential equations is associated with the given matrix and after Laplace transform the individual transformed components are shown to be special Padé approximants.     

On the Definition of Surface Potentials for Finite-Difference Operators

For a class of linear constant-coefficient finite-difference operators of the second order, we introduce the concepts similar to those of conventional single- and double-layer potentials for differential operators. The discrete potentials are defined completely independently of any notion related to the approximation of the continuous potentials on the grid. We rather use an approach based on differentiating, and then inverting the differentiation of, a function with surface discontinuity of a particular kind, which is the most general way of introducing surface potentials in the theory of distributions. The resulting finite-difference surface potentials appear to be solutions of the corresponding system of linear algebraic equations driven by special source terms. The properties of the discrete potentials in many respects resemble those of the corresponding continuous potentials. Primarily, this pertains to the possibility of representing a given solution to the homogeneous equation on the domain as a variety of surface potentials with the density defined on the domain's boundary. At the same time, the discrete surface potentials can be interpreted as one specific realization of the generalized potentials of Calderon's type, and consequently, their approximation properties can be studied independently in the framework of the difference potentials method by Ryaben'kii. The motivation for introducing and analyzing the discrete surface potentials was provided by the problems of active shielding and control of sound, in which the aforementioned source terms that drive the potentials are interpreted as the acoustic control sources that cancel out the unwanted noise on a predetermined region of interest.     

Programs for the approximation of real and imaginary single- and multi-valued functions by means of Hermite-Padé-approximants

We present programs for the calculation and evaluation of special type Hermite-Padé-approximations. They allow the user to either numerically approximate multi-valued functions represented by a formal series expansion or to compute explicit approximants for them. The approximation scheme is based on Hermite-Padé polynomials and includes both Padé and algebraic approximants as limiting cases. The algorithm for the computation of the Hermite-Padé polynomials is based on a set of recursive equations which were derived from a generalization of continued fractions. The approximations retain their validity even on the cuts of the complex Riemann surface which allows for example the calculation of resonances in quantum mechanical problems. The programs also allow for the construction of multi-series approximations which can be more powerful than most summation methods.

Program summary

Title of program: hp.srCatalogue identifier: ADSOProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSOProgram obtainable from: CPC Program Library, Queen's University Belfast, Northern IrelandLicensing provisions: Persons requesting the program must sign the standard CPC non-profit use licenseComputer: Sun Ultra 10Installation: Computing Center, University of Regensburg, GermanyOperating System: Sun Solaris 7.0Program language used: MapleV.5Distribution format: tar gzip fileMemory required to execute with typical data: 32 MB; the program itself needs only about 20 kBNumber of bits in a word: 32No. of processors used: 1Has the code been vectorized?: noNo. of bytes in distributed program, including test data etc.: 38194No. of lines in distributed program, including test data, etc.: 4258Nature of physical problem: Many physical and chemical quantum systems lead to the problem of evaluating a function for which only a limited series expansion is known. These functions can be numerically approximated by summation methods even if the corresponding series is only asymptotic. With the help of Hermite-Padé-approximants many different approximation schemes can be realized. Padé and algebraic approximants are just well-known examples. Hermite-Padé-approximants combine the advantages of highly accurate numerical results with the additional advantage of being able to sum complex multi-valued functions.Method of solution: Special type Hermite-Padé polynomials are calculated for a set of divergent series. These polynomials are then used to implicitly define approximants for one of the functions of this set. This approximant can be numerically evaluated at any point of the Riemann surface of this function. For an approximation order not greater than 3 the approximants can alternatively be expressed in closed form and then be used to approximate the desired function on its complete Riemann surface.Restriction on the complexity of the problem: In principle, the algorithm is only limited by the available memory and speed of the underlying computer system. Furthermore the achievable accuracy of the approximation only depends on the number of known series coefficients of the function to be approximated assuming of course that these coefficients are known with enough accuracy.Typical running time: 10 minutes with parameters comparable to the testrunsUnusual features of the program: none     

Computing isophotos of surface of revolution and canal surface

Isophote of a surface consists of a loci of surface points whose normal vectors form a constant angle with a given fixed vector. It also serves as a silhouette curve when the constant angle is given as π/2. We present efficient and robust algorithms to compute isophotes of a surface of revolution and a canal surface. For the two kinds of surfaces, each point on the isophote is derived by a closed-form solution. To find each connected component in the isophote, we utilize the feature of surface normals. Both surfaces are decomposed into a set of circles, where the surface normal vectors at points on each circle construct a cone. The vectors which form a constant angle with given fixed vector construct another cone. We compute the parametric range of the connected component of the isophote by computing the parametric values of the surface which derive the tangential intersection of these two cones.     

Approximation of multivariable linear systems with impulse response and autocorrelation sequences

This paper considers the construction of approximants of multi-input-multi-output, discrete-time linear systems from the finite data of the impulse response and autocorrelation sequences. In the approximation of a multivariable linear system, it is common practice to use a finite portion of its impulse response sequence. This is formally equivalent to the Padé approximation technique, which may produce unstable approximants, even though the original system is stable. Mullis and Roberts proposed a new method, which yields stable approximants, in connection with approximation of digital filters. This is, however, restricted to the single-input-single-output case. This paper extends their method to the multi-input-multi-output case and shows a fast recursive algorithm to construct stable approximants of linear systems.     

On finite-state approximants for probabilistic computation tree logic

We generalize the familiar semantics for probabilistic computation tree logic from finite-state to infinite-state labelled Markov chains such that formulas are interpreted as measurable sets. Then we show how to synthesize finite-state abstractions which are sound for full probabilistic computation tree logic and in which measures are approximated by monotone set functions. This synthesis of sound finite-state approximants also applies to finite-state systems and is a probabilistic analogue of predicate abstraction. Sufficient and always realizable conditions are identified for obtaining optimal such abstractions for probabilistic propositional modal logic.     

Global approximation for some functions

Approximate closed form representations of functions are useful for mathematical manipulations. Nonlinear sequence transforms can be used to evaluate the function using a few terms of the series representation of the function and these transforms can be used for functions with complex argument as well. Moreover, if an asymptotic expansion of the function is available, an approximant for the function, valid for the entire range of the variable, can be obtained with Padé approximants as well as Levin and Weniger transforms. In addition, one can obtain an approximation for a function using quadratic Padé approximation which is also valid for the entire range of the variable. We demonstrate this for some functions frequently encountered in scientific problems. These include the error function, the Fresnel integral, the Dawson integral, the Euler integral and the elliptic integral. A comparison is made between the approximants obtained with Padé approximants and those generated by Levin and Weniger transforms.     

Padé error estimates for the logarithm of a matrix

The error of Padé approximations to the logarithm of a matrix and related hypergeometric functions is analysed. By obtaining an exact error expansion with positive coefficients, it is shown that the error in the matrix approximation at X is always less than the scalar approximation error at x, when ∥X∥ < x. A more detailed analysis, involving the interlacing properties of the zeros of the Padé denominator polynomials, shows that for a given order of approximation, the diagonal Padé approximants are the most accurate. Similarly, knowing that the denominator zeros must lie in the interval (1,∞) leads to a simple upper bound on the condition number of the matrix denominator polynomial, which is a crucial indicator of how accurately the matrix Padé approximants can be evaluated numerically. In this respect the Padé approximants to the logarithm are very well conditioned for ∥X∥ < 0·25. This latter condition can be ensured by using the ‘inverse scaling and squaring’ procedure for evaluating the logarithm.     

Tangential Distance Fields for Mesh Silhouette Problems

We consider a tangent-space representation of surfaces that maps each point on a surface to the tangent plane of the surface at that point. Such representations are known to facilitate the solution of several visibility problems, in particular, those involving silhouette analysis. In this paper, we introduce a novel class of distance fields for a given surface defined by its tangent planes. At each point in space, we assign a scalar value which is a weighted sum of distances to these tangent planes. We call the resulting scalar field a 'tangential distance field' (TDF). When applied to triangle mesh models, the tangent planes become supporting planes of the mesh triangles. The weighting scheme used to construct a TDF for a given mesh and the way the TDF is utilized can be closely tailored to a specific application. At the same time, the TDFs are continuous, lending themselves to standard optimization techniques such as greedy local search, thus leading to efficient algorithms. In this paper, we use four applications to illustrate the benefit of using TDFs: multi-origin silhouette extraction in Hough space, silhouette-based view point selection, camera path planning and light source placement.