Fast track segment finding in the Monitored Drift Tubes (MDT) of the ATLAS Muon Spectrometer using a Legendre transform algorithm

CERN Document Server

Ntekas, Konstantinos; The ATLAS collaboration

2018-01-01

Many of the physics goals of ATLAS in the High Luminosity LHC era, including precision studies of the Higgs boson, require an unprescaled single muon trigger with a 20 GeV threshold. The selectivity of the current ATLAS first-level muon trigger is limited by the moderate spatial resolution of the muon trigger chambers. By incorporating the precise tracking of the MDT, the muon transverse momentum can be measured with an accuracy close to that of the offline reconstruction at the trigger level, sharpening the trigger turn-on curves and reducing the single muon trigger rate. A novel algorithm is proposed which reconstructs segments from MDT hits in an FPGA and find tracks within the tight latency constraints of the ATLAS first-level muon trigger. The algorithm represents MDT drift circles as curves in the Legendre space and returns one or more segment lines tangent to the maximum possible number of drift circles.  This algorithm is implemented without the need of resource and time consuming hit position calcul...

Essential imposition of Neumann condition in Galerkin-Legendre elliptic solvers

CERN Document Server

Auteri, F; Quartapelle, L

2003-01-01

A new Galerkin-Legendre direct spectral solver for the Neumann problem associated with Laplace and Helmholtz operators in rectangular domains is presented. The algorithm differs from other Neumann spectral solvers by the high sparsity of the matrices, exploited in conjunction with the direct product structure of the problem. The homogeneous boundary condition is satisfied exactly by expanding the unknown variable into a polynomial basis of functions which are built upon the Legendre polynomials and have a zero slope at the interval extremes. A double diagonalization process is employed pivoting around the eigenstructure of the pentadiagonal mass matrices in both directions, instead of the full stiffness matrices encountered in the classical variational formulation of the problem with a weak natural imposition of the derivative boundary condition. Nonhomogeneous Neumann data are accounted for by means of a lifting. Numerical results are given to illustrate the performance of the proposed spectral elliptic solv...

Fast and Accurate Computation of Gauss--Legendre and Gauss--Jacobi Quadrature Nodes and Weights

KAUST Repository

Hale, Nicholas; Townsend, Alex

2013-01-01

An efficient algorithm for the accurate computation of Gauss-Legendre and Gauss-Jacobi quadrature nodes and weights is presented. The algorithm is based on Newton's root-finding method with initial guesses and function evaluations computed via asymptotic formulae. The n-point quadrature rule is computed in O(n) operations to an accuracy of essentially double precision for any n ≥ 100. © 2013 Society for Industrial and Applied Mathematics.

Fast and Accurate Computation of Gauss--Legendre and Gauss--Jacobi Quadrature Nodes and Weights

KAUST Repository

Hale, Nicholas

2013-03-06

An efficient algorithm for the accurate computation of Gauss-Legendre and Gauss-Jacobi quadrature nodes and weights is presented. The algorithm is based on Newton\\'s root-finding method with initial guesses and function evaluations computed via asymptotic formulae. The n-point quadrature rule is computed in O(n) operations to an accuracy of essentially double precision for any n ≥ 100. © 2013 Society for Industrial and Applied Mathematics.

Higher-Order Hierarchical Legendre Basis Functions in Applications

DEFF Research Database (Denmark)

Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter

2007-01-01

The higher-order hierarchical Legendre basis functions have been developed for effective solution of integral equations with the method of moments. They are derived from orthogonal Legendre polynomials modified to enforce normal continuity between neighboring mesh elements, while preserving a high...

Superiority of legendre polynomials to Chebyshev polynomial in ...

African Journals Online (AJOL)

In this paper, we proved the superiority of Legendre polynomial to Chebyshev polynomial in solving first order ordinary differential equation with rational coefficient. We generated shifted polynomial of Chebyshev, Legendre and Canonical polynomials which deal with solving differential equation by first choosing Chebyshev ...

Generalized Pseudospectral Method and Zeros of Orthogonal Polynomials

Directory of Open Access Journals (Sweden)

Oksana Bihun

2018-01-01

Full Text Available Via a generalization of the pseudospectral method for numerical solution of differential equations, a family of nonlinear algebraic identities satisfied by the zeros of a wide class of orthogonal polynomials is derived. The generalization is based on a modification of pseudospectral matrix representations of linear differential operators proposed in the paper, which allows these representations to depend on two, rather than one, sets of interpolation nodes. The identities hold for every polynomial family pνxν=0∞ orthogonal with respect to a measure supported on the real line that satisfies some standard assumptions, as long as the polynomials in the family satisfy differential equations Apν(x=qν(xpν(x, where A is a linear differential operator and each qν(x is a polynomial of degree at most n0∈N; n0 does not depend on ν. The proposed identities generalize known identities for classical and Krall orthogonal polynomials, to the case of the nonclassical orthogonal polynomials that belong to the class described above. The generalized pseudospectral representations of the differential operator A for the case of the Sonin-Markov orthogonal polynomials, also known as generalized Hermite polynomials, are presented. The general result is illustrated by new algebraic relations satisfied by the zeros of the Sonin-Markov polynomials.

Pseudo-spectral method using rotated staggered grid for elastic wave propagation in 3D arbitrary anisotropic media

KAUST Repository

Zou, Peng

2017-05-10

Staggering grid is a very effective way to reduce the Nyquist errors and to suppress the non-causal ringing artefacts in the pseudo-spectral solution of first-order elastic wave equations. However, the straightforward use of a staggered-grid pseudo-spectral method is problematic for simulating wave propagation when the anisotropy level is greater than orthorhombic or when the anisotropic symmetries are not aligned with the computational grids. Inspired by the idea of rotated staggered-grid finite-difference method, we propose a modified pseudo-spectral method for wave propagation in arbitrary anisotropic media. Compared with an existing remedy of staggered-grid pseudo-spectral method based on stiffness matrix decomposition and a possible alternative using the Lebedev grids, the rotated staggered-grid-based pseudo-spectral method possesses the best balance between the mitigation of artefacts and efficiency. A 2D example on a transversely isotropic model with tilted symmetry axis verifies its effectiveness to suppress the ringing artefacts. Two 3D examples of increasing anisotropy levels demonstrate that the rotated staggered-grid-based pseudo-spectral method can successfully simulate complex wavefields in such anisotropic formations.

Benchmarking and scaling studies of pseudospectral code Tarang ...

Indian Academy of Sciences (India)

Tarang is a general-purpose pseudospectral parallel code for simulating flows involving fluids, magnetohydrodynamics, and Rayleigh–Bénard convection in turbulence and instability regimes. In this paper we present code validation and benchmarking results of Tarang. We performed our simulations on 10243, 20483, and ...

A multidimensional pseudospectral method for optimal control of quantum ensembles

International Nuclear Information System (INIS)

Ruths, Justin; Li, Jr-Shin

2011-01-01

In our previous work, we have shown that the pseudospectral method is an effective and flexible computation scheme for deriving pulses for optimal control of quantum systems. In practice, however, quantum systems often exhibit variation in the parameters that characterize the system dynamics. This leads us to consider the control of an ensemble (or continuum) of quantum systems indexed by the system parameters that show variation. We cast the design of pulses as an optimal ensemble control problem and demonstrate a multidimensional pseudospectral method with several challenging examples of both closed and open quantum systems from nuclear magnetic resonance spectroscopy in liquid. We give particular attention to the ability to derive experimentally viable pulses of minimum energy or duration.

Legendre-tau approximations for functional differential equations

Science.gov (United States)

Ito, K.; Teglas, R.

1986-01-01

The numerical approximation of solutions to linear retarded functional differential equations are considered using the so-called Legendre-tau method. The functional differential equation is first reformulated as a partial differential equation with a nonlocal boundary condition involving time-differentiation. The approximate solution is then represented as a truncated Legendre series with time-varying coefficients which satisfy a certain system of ordinary differential equations. The method is very easy to code and yields very accurate approximations. Convergence is established, various numerical examples are presented, and comparison between the latter and cubic spline approximation is made.

Pseudo-spectral method using rotated staggered grid for elastic wave propagation in 3D arbitrary anisotropic media

KAUST Repository

Zou, Peng; Cheng, Jiubing

2017-01-01

-difference method, we propose a modified pseudo-spectral method for wave propagation in arbitrary anisotropic media. Compared with an existing remedy of staggered-grid pseudo-spectral method based on stiffness matrix decomposition and a possible alternative using

Efficient pseudospectral methods for density functional calculations

International Nuclear Information System (INIS)

Murphy, R. B.; Cao, Y.; Beachy, M. D.; Ringnalda, M. N.; Friesner, R. A.

2000-01-01

Novel improvements of the pseudospectral method for assembling the Coulomb operator are discussed. These improvements consist of a fast atom centered multipole method and a variation of the Head-Gordan J-engine analytic integral evaluation. The details of the methodology are discussed and performance evaluations presented for larger molecules within the context of DFT energy and gradient calculations. (c) 2000 American Institute of Physics

On the analytic continuation of functions defined by Legendre series

International Nuclear Information System (INIS)

Grinstein, F.F.

1981-07-01

An infinite diagonal sequence of Punctual Pade Approximants is considered for the approximate analytical continuation of a function defined by a formal Legendre series. The technique is tested in the case of two series with exactly known analytical sum: the generating function for Legendre polynomials and the Coulombian scattering amplitude. (author)

Computation of temperature-dependent legendre moments of a double-differential elastic cross section

International Nuclear Information System (INIS)

Arbanas, G.; Dunn, M.E.; Larson, N.M.; Leal, L.C.; Williams, M.L.; Becker, B.; Dagan, R.

2011-01-01

A general expression for temperature-dependent Legendre moments of a double-differential elastic scattering cross section was derived by Ouisloumen and Sanchez [Nucl. Sci. Eng. 107, 189-200 (1991)]. Attempts to compute this expression are hindered by the three-fold nested integral, limiting their practical application to just the zeroth Legendre moment of an isotropic scattering. It is shown that the two innermost integrals could be evaluated analytically to all orders of Legendre moments, and for anisotropic scattering, by a recursive application of the integration by parts method. For this method to work, the anisotropic angular distribution in the center of mass is expressed as an expansion in Legendre polynomials. The first several Legendre moments of elastic scattering of neutrons on 238 U are computed at T=1000 K at incoming energy 6.5 eV for isotropic scattering in the center of mass frame. Legendre moments of the anisotropic angular distribution given via Blatt-Biedenharn coefficients are computed at 1 keV. The results are in agreement with those computed by the Monte Carlo method. (author)

Congruences concerning Legendre polynomials III

OpenAIRE

Sun, Zhi-Hong

2010-01-01

Let $p>3$ be a prime, and let $R_p$ be the set of rational numbers whose denominator is coprime to $p$. Let $\\{P_n(x)\\}$ be the Legendre polynomials. In this paper we mainly show that for $m,n,t\\in R_p$ with $m\

A pseudospectral collocation time-domain method for diffractive optics

DEFF Research Database (Denmark)

Dinesen, P.G.; Hesthaven, J.S.; Lynov, Jens-Peter

2000-01-01

We present a pseudospectral method for the analysis of diffractive optical elements. The method computes a direct time-domain solution of Maxwell's equations and is applied to solving wave propagation in 2D diffractive optical elements. (C) 2000 IMACS. Published by Elsevier Science B.V. All rights...

Long-range transmission of pollutants simulated by a two-dimensional pseudospectral dispersion model

International Nuclear Information System (INIS)

Prahm, L.P.; Christensen, O.

1977-01-01

The pseudospectral dispersion model (Christensen and Prahm, 1976) is adapted for simulation of the long-range transmission of sulphur pollutants in the European region, covering an area of about 4000 km x 4000 km. Regional ''background'' concentrations of sulphur oxides are found to be highly dependent on distant sources and to correlate poorly with local source strength during the considered three- and four-day episodes. The simulation is based on emission data, given in squares of about 50 km x 50 km and on synoptic wind fields derived from observed wind velocities of the 850 mb level and the surface level. The two-dimensional model includes a constant vertical mixing depth. Appropriate values for the deposition and the transformation rates of SO 2 and SO/sup 4 are used. The concentration of pollutants computed from the two-dimensional pseudospectral dispersion model reflects the variable meteorological conditions. Computed concentrations are compared with measurements, giving spatial correlations between 0.4 and 0.8 for more than 400 ground-based 24 h mean values, and a spatial correlation of 0.9 for eight aircraft samples averaged over approx.30 min. A discussion of the influence of different sources of error in the model simulation is given. The high numerical accuracy of the pseudospectral model is combined with a modest consumption of CPU computer time. This study is the first application of the pseudospectral dispersion model which compares computed concentrations with measured field data. The model has possible applications as a tool for assessment of the impact of both national and international emission regulation strategies

Pseudospectral methods on a semi-infinite interval with application to the hydrogen atom: a comparison of the mapped Fourier-sine method with Laguerre series and rational Chebyshev expansions

International Nuclear Information System (INIS)

Boyd, John P.; Rangan, C.; Bucksbaum, P.H.

2003-01-01

The Fourier-sine-with-mapping pseudospectral algorithm of Fattal et al. [Phys. Rev. E 53 (1996) 1217] has been applied in several quantum physics problems. Here, we compare it with pseudospectral methods using Laguerre functions and rational Chebyshev functions. We show that Laguerre and Chebyshev expansions are better suited for solving problems in the interval r in R set of [0,∞] (for example, the Coulomb-Schroedinger equation), than the Fourier-sine-mapping scheme. All three methods give similar accuracy for the hydrogen atom when the scaling parameter L is optimum, but the Laguerre and Chebyshev methods are less sensitive to variations in L. We introduce a new variant of rational Chebyshev functions which has a more uniform spacing of grid points for large r, and gives somewhat better results than the rational Chebyshev functions of Boyd [J. Comp. Phys. 70 (1987) 63

SpF: Enabling Petascale Performance for Pseudospectral Dynamo Models

Science.gov (United States)

Jiang, W.; Clune, T.; Vriesema, J.; Gutmann, G.

2013-12-01

Pseudospectral (PS) methods possess a number of characteristics (e.g., efficiency, accuracy, natural boundary conditions) that are extremely desirable for dynamo models. Unfortunately, dynamo models based upon PS methods face a number of daunting challenges, which include exposing additional parallelism, leveraging hardware accelerators, exploiting hybrid parallelism, and improving the scalability of global memory transposes. Although these issues are a concern for most models, solutions for PS methods tend to require far more pervasive changes to underlying data and control structures. Further, improvements in performance in one model are difficult to transfer to other models, resulting in significant duplication of effort across the research community. We have developed an extensible software framework for pseudospectral methods called SpF that is intended to enable extreme scalability and optimal performance. High-level abstractions provided by SpF unburden applications of the responsibility of managing domain decomposition and load balance while reducing the changes in code required to adapt to new computing architectures. The key design concept in SpF is that each phase of the numerical calculation is partitioned into disjoint numerical 'kernels' that can be performed entirely in-processor. The granularity of domain-decomposition provided by SpF is only constrained by the data-locality requirements of these kernels. SpF builds on top of optimized vendor libraries for common numerical operations such as transforms, matrix solvers, etc., but can also be configured to use open source alternatives for portability. SpF includes several alternative schemes for global data redistribution and is expected to serve as an ideal testbed for further research into optimal approaches for different network architectures. In this presentation, we will describe the basic architecture of SpF as well as preliminary performance data and experience with adapting legacy dynamo codes

Comment on 'Analytical results for a Bessel function times Legendre polynomials class integrals'

International Nuclear Information System (INIS)

Cregg, P J; Svedlindh, P

2007-01-01

A result is obtained, stemming from Gegenbauer, where the products of certain Bessel functions and exponentials are expressed in terms of an infinite series of spherical Bessel functions and products of associated Legendre functions. Closed form solutions for integrals involving Bessel functions times associated Legendre functions times exponentials, recently elucidated by Neves et al (J. Phys. A: Math. Gen. 39 L293), are then shown to result directly from the orthogonality properties of the associated Legendre functions. This result offers greater flexibility in the treatment of classical Heisenberg chains and may do so in other problems such as occur in electromagnetic diffraction theory. (comment)

Shock wave interaction with turbulence: Pseudospectral simulations

International Nuclear Information System (INIS)

Buckingham, A.C.

1986-01-01

Shock waves amplify pre-existing turbulence. Shock tube and shock wave boundary layer interaction experiments provide qualitative confirmation. However, shock pressure, temperature, and rapid transit complicate direct measurement. Computational simulations supplement the experimental data base and help isolate the mechanisms responsible. Simulations and experiments, particularly under reflected shock wave conditions, significantly influence material mixing. In these pseudospectral Navier-Stokes simulations the shock wave is treated as either a moving (tracked or fitted) domain boundary. The simulations assist development of code mix models. Shock Mach number and pre-existing turbulence intensity initially emerge as key parameters. 20 refs., 8 figs

On computation and use of Fourier coefficients for associated Legendre functions

Science.gov (United States)

Gruber, Christian; Abrykosov, Oleh

2016-06-01

The computation of spherical harmonic series in very high resolution is known to be delicate in terms of performance and numerical stability. A major problem is to keep results inside a numerical range of the used data type during calculations as under-/overflow arises. Extended data types are currently not desirable since the arithmetic complexity will grow exponentially with higher resolution levels. If the associated Legendre functions are computed in the spectral domain, then regular grid transformations can be applied to be highly efficient and convenient for derived quantities as well. In this article, we compare three recursive computations of the associated Legendre functions as trigonometric series, thereby ensuring a defined numerical range for each constituent wave number, separately. The results to a high degree and order show the numerical strength of the proposed method. First, the evaluation of Fourier coefficients of the associated Legendre functions has been done with respect to the floating-point precision requirements. Secondly, the numerical accuracy in the cases of standard double and long double precision arithmetic is demonstrated. Following Bessel's inequality the obtained accuracy estimates of the Fourier coefficients are directly transferable to the associated Legendre functions themselves and to derived functionals as well. Therefore, they can provide an essential insight to modern geodetic applications that depend on efficient spherical harmonic analysis and synthesis beyond [5~× ~5] arcmin resolution.

OpenPSTD : The open source implementation of the pseudospectral time-domain method

NARCIS (Netherlands)

Krijnen, T.; Hornikx, M.C.J.; Borkowski, B.

2014-01-01

An open source implementation of the pseudospectral time-domain method for the propagation of sound is presented, which is geared towards applications in the built environment. Being a wavebased method, PSTD captures phenomena like diffraction, but maintains efficiency in processing time and memory

Hybrid Fourier pseudospectral/discontinuous Galerkin time-domain method for arbitrary boundary conditions

NARCIS (Netherlands)

Pagan Munoz, R.; Hornikx, M.C.J.

The wave-based Fourier Pseudospectral time-domain (Fourier-PSTD) method was shown to be an effective way of modeling outdoor acoustic propagation problems as described by the linearized Euler equations (LEE), but is limited to real-valued frequency independent boundary conditions and predominantly

OpenPSTD : The open source pseudospectral time-domain method for acoustic propagation

NARCIS (Netherlands)

Hornikx, M.C.J.; Krijnen, T.F.; van Harten, L.

2016-01-01

An open source implementation of the Fourier pseudospectral time-domain (PSTD) method for computing the propagation of sound is presented, which is geared towards applications in the built environment. Being a wave-based method, PSTD captures phenomena like diffraction, but maintains efficiency in

Legendre transformations and Clairaut-type equations

Energy Technology Data Exchange (ETDEWEB)

Lavrov, Peter M., E-mail: lavrov@tspu.edu.ru [Tomsk State Pedagogical University, Kievskaya St. 60, 634061 Tomsk (Russian Federation); National Research Tomsk State University, Lenin Av. 36, 634050 Tomsk (Russian Federation); Merzlikin, Boris S., E-mail: merzlikin@tspu.edu.ru [National Research Tomsk Polytechnic University, Lenin Av. 30, 634050 Tomsk (Russian Federation)

2016-05-10

It is noted that the Legendre transformations in the standard formulation of quantum field theory have the form of functional Clairaut-type equations. It is shown that in presence of composite fields the Clairaut-type form holds after loop corrections are taken into account. A new solution to the functional Clairaut-type equation appearing in field theories with composite fields is found.

Matrix form of Legendre polynomials for solving linear integro-differential equations of high order

Science.gov (United States)

Kammuji, M.; Eshkuvatov, Z. K.; Yunus, Arif A. M.

2017-04-01

This paper presents an effective approximate solution of high order of Fredholm-Volterra integro-differential equations (FVIDEs) with boundary condition. Legendre truncated series is used as a basis functions to estimate the unknown function. Matrix operation of Legendre polynomials is used to transform FVIDEs with boundary conditions into matrix equation of Fredholm-Volterra type. Gauss Legendre quadrature formula and collocation method are applied to transfer the matrix equation into system of linear algebraic equations. The latter equation is solved by Gauss elimination method. The accuracy and validity of this method are discussed by solving two numerical examples and comparisons with wavelet and methods.

The Rational Third-Kind Chebyshev Pseudospectral Method for the Solution of the Thomas-Fermi Equation over Infinite Interval

Directory of Open Access Journals (Sweden)

Majid Tavassoli Kajani

2013-01-01

Full Text Available We propose a pseudospectral method for solving the Thomas-Fermi equation which is a nonlinear ordinary differential equation on semi-infinite interval. This approach is based on the rational third-kind Chebyshev pseudospectral method that is indeed a combination of Tau and collocation methods. This method reduces the solution of this problem to the solution of a system of algebraic equations. Comparison with some numerical solutions shows that the present solution is highly accurate.

Chudnovsky-Ramanujan Type Formulae for the Legendre Family

OpenAIRE

Chen, Imin; Glebov, Gleb

2017-01-01

We apply the method established in our previous work to derive a Chudnovsky-Ramanujan type formula for the Legendre family of elliptic curves. As a result, we prove two identities for $1/\\pi$ in terms of hypergeometric functions.

On Parameter Differentiation for Integral Representations of Associated Legendre Functions

Directory of Open Access Journals (Sweden)

Howard S. Cohl

2011-05-01

Full Text Available For integral representations of associated Legendre functions in terms of modified Bessel functions, we establish justification for differentiation under the integral sign with respect to parameters. With this justification, derivatives for associated Legendre functions of the first and second kind with respect to the degree are evaluated at odd-half-integer degrees, for general complex-orders, and derivatives with respect to the order are evaluated at integer-orders, for general complex-degrees. We also discuss the properties of the complex function f: C{−1,1}→C given by f(z=z/((z+1^{1/2}(z−1^{1/2}.

A Legendre Wavelet Spectral Collocation Method for Solving Oscillatory Initial Value Problems

Directory of Open Access Journals (Sweden)

A. Karimi Dizicheh

2013-01-01

wavelet suitable for large intervals, and then the Legendre-Guass collocation points of the Legendre wavelet are derived. Using this strategy, the iterative spectral method converts the differential equation to a set of algebraic equations. Solving these algebraic equations yields an approximate solution for the differential equation. The proposed method is illustrated by some numerical examples, and the result is compared with the exponentially fitted Runge-Kutta method. Our proposed method is simple and highly accurate.

Discrete fractional solutions of a Legendre equation

Science.gov (United States)

Yılmazer, Resat

2018-01-01

One of the most popular research interests of science and engineering is the fractional calculus theory in recent times. Discrete fractional calculus has also an important position in fractional calculus. In this work, we acquire new discrete fractional solutions of the homogeneous and non homogeneous Legendre differential equation by using discrete fractional nabla operator.

Tests of a numerical algorithm for the linear instability study of flows on a sphere

Energy Technology Data Exchange (ETDEWEB)

Perez Garcia, Ismael; Skiba, Yuri N [Univerisidad Nacional Autonoma de Mexico, Mexico, D.F. (Mexico)

2001-04-01

A numerical algorithm for the normal mode instability of a steady nondivergent flow on a rotating sphere is developed. The algorithm accuracy is tested with zonal solutions of the nonlinear barotropic vorticity equation (Legendre polynomials, zonal Rossby-Harwitz waves and monopole modons). [Spanish] Ha sido desarrollado un algoritmo numerico para estudiar la inestabilidad lineal de un flujo estacionario no divergente en una esfera en rotacion. La precision del algoritmo se prueba con soluciones zonales de la ecuacion no lineal de vorticidad barotropica (polinomios de Legendre, ondas zonales Rossby-Harwitz y modones monopolares).

Mixed Legendre moments and discrete scattering cross sections for anisotropy representation

International Nuclear Information System (INIS)

Calloo, A.; Vidal, J. F.; Le Tellier, R.; Rimpault, G.

2012-01-01

This paper deals with the resolution of the integro-differential form of the Boltzmann transport equation for neutron transport in nuclear reactors. In multigroup theory, deterministic codes use transfer cross sections which are expanded on Legendre polynomials. This modelling leads to negative values of the transfer cross section for certain scattering angles, and hence, the multigroup scattering source term is wrongly computed. The first part compares the convergence of 'Legendre-expanded' cross sections with respect to the order used with the method of characteristics (MOC) for Pressurised Water Reactor (PWR) type cells. Furthermore, the cross section is developed using piecewise-constant functions, which better models the multigroup transfer cross section and prevents the occurrence of any negative value for it. The second part focuses on the method of solving the transport equation with the above-mentioned piecewise-constant cross sections for lattice calculations for PWR cells. This expansion thereby constitutes a 'reference' method to compare the conventional Legendre expansion to, and to determine its pertinence when applied to reactor physics calculations. (authors)

A fast algorithm for forward-modeling of gravitational fields in spherical coordinates with 3D Gauss-Legendre quadrature

Science.gov (United States)

Zhao, G.; Liu, J.; Chen, B.; Guo, R.; Chen, L.

2017-12-01

Forward modeling of gravitational fields at large-scale requires to consider the curvature of the Earth and to evaluate the Newton's volume integral in spherical coordinates. To acquire fast and accurate gravitational effects for subsurface structures, subsurface mass distribution is usually discretized into small spherical prisms (called tesseroids). The gravity fields of tesseroids are generally calculated numerically. One of the commonly used numerical methods is the 3D Gauss-Legendre quadrature (GLQ). However, the traditional GLQ integration suffers from low computational efficiency and relatively poor accuracy when the observation surface is close to the source region. We developed a fast and high accuracy 3D GLQ integration based on the equivalence of kernel matrix, adaptive discretization and parallelization using OpenMP. The equivalence of kernel matrix strategy increases efficiency and reduces memory consumption by calculating and storing the same matrix elements in each kernel matrix just one time. In this method, the adaptive discretization strategy is used to improve the accuracy. The numerical investigations show that the executing time of the proposed method is reduced by two orders of magnitude compared with the traditional method that without these optimized strategies. High accuracy results can also be guaranteed no matter how close the computation points to the source region. In addition, the algorithm dramatically reduces the memory requirement by N times compared with the traditional method, where N is the number of discretization of the source region in the longitudinal direction. It makes the large-scale gravity forward modeling and inversion with a fine discretization possible.

Legendre Wavelet Operational Matrix Method for Solution of Riccati Differential Equation

Directory of Open Access Journals (Sweden)

S. Balaji

2014-01-01

Full Text Available A Legendre wavelet operational matrix method (LWM is presented for the solution of nonlinear fractional-order Riccati differential equations, having variety of applications in quantum chemistry and quantum mechanics. The fractional-order Riccati differential equations converted into a system of algebraic equations using Legendre wavelet operational matrix. Solutions given by the proposed scheme are more accurate and reliable and they are compared with recently developed numerical, analytical, and stochastic approaches. Comparison shows that the proposed LWM approach has a greater performance and less computational effort for getting accurate solutions. Further existence and uniqueness of the proposed problem are given and moreover the condition of convergence is verified.

Szegö Kernels and Asymptotic Expansions for Legendre Polynomials

Directory of Open Access Journals (Sweden)

Roberto Paoletti

2017-01-01

Full Text Available We present a geometric approach to the asymptotics of the Legendre polynomials Pk,n+1, based on the Szegö kernel of the Fermat quadric hypersurface, leading to complete asymptotic expansions holding on expanding subintervals of [-1,1].

Benchmarking and scaling studies of pseudospectral code Tarang for turbulence simulations

KAUST Repository

VERMA, MAHENDRA K

2013-09-21

Tarang is a general-purpose pseudospectral parallel code for simulating flows involving fluids, magnetohydrodynamics, and Rayleigh–Bénard convection in turbulence and instability regimes. In this paper we present code validation and benchmarking results of Tarang. We performed our simulations on 10243, 20483, and 40963 grids using the HPC system of IIT Kanpur and Shaheen of KAUST. We observe good ‘weak’ and ‘strong’ scaling for Tarang on these systems.

Benchmarking and scaling studies of pseudospectral code Tarang for turbulence simulations

KAUST Repository

VERMA, MAHENDRA K; CHATTERJEE, ANANDO; REDDY, K SANDEEP; YADAV, RAKESH K; PAUL, SUPRIYO; CHANDRA, MANI; Samtaney, Ravi

2013-01-01

Tarang is a general-purpose pseudospectral parallel code for simulating flows involving fluids, magnetohydrodynamics, and Rayleigh–Bénard convection in turbulence and instability regimes. In this paper we present code validation and benchmarking results of Tarang. We performed our simulations on 10243, 20483, and 40963 grids using the HPC system of IIT Kanpur and Shaheen of KAUST. We observe good ‘weak’ and ‘strong’ scaling for Tarang on these systems.

Solved problems in analysis as applied to gamma, beta, Legendre and Bessel functions

CERN Document Server

Farrell, Orin J

2013-01-01

Nearly 200 problems, each with a detailed, worked-out solution, deal with the properties and applications of the gamma and beta functions, Legendre polynomials, and Bessel functions. The first two chapters examine gamma and beta functions, including applications to certain geometrical and physical problems such as heat-flow in a straight wire. The following two chapters treat Legendre polynomials, addressing applications to specific series expansions, steady-state heat-flow temperature distribution, gravitational potential of a circular lamina, and application of Gauss's mechanical quadrature

Multiphase Return Trajectory Optimization Based on Hybrid Algorithm

Directory of Open Access Journals (Sweden)

Yi Yang

2016-01-01

Full Text Available A hybrid trajectory optimization method consisting of Gauss pseudospectral method (GPM and natural computation algorithm has been developed and utilized to solve multiphase return trajectory optimization problem, where a phase is defined as a subinterval in which the right-hand side of the differential equation is continuous. GPM converts the optimal control problem to a nonlinear programming problem (NLP, which helps to improve calculation accuracy and speed of natural computation algorithm. Through numerical simulations, it is found that the multiphase optimal control problem could be solved perfectly.

Evaluate More General Integrals Involving Universal Associated Legendre Polynomials via Taylor's Theorem

Institute of Scientific and Technical Information of China (English)

G.Ya(n)ez-Navarro; Guo-Hua Sun; Dong-Sheng Sun; Chang-Yuan Chen; Shi-Hai Dong

2017-01-01

A few important integrals involving the product of two universal associated Legendre polynomials Pl'm'(x),Pk'n'(x) and x2a(1-x2)-p-1,xb(1 ±x)-p-1 and xc(1-x2)-p-1 (1 ±-x) are evaluated using the operator form of Taylor's theorem and an integral over a single universal associated Legendre polynomial.These integrals are more general since the quantum numbers are unequal,i.e.l'≠ k'and m'≠ n'.Their selection rules are also given.We also verify the correctness of those integral formulas numerically.

Transformation formulas for legendre coefficients of double-differential cross sections

International Nuclear Information System (INIS)

Shi Xiangjun; Zhang Jingshang

1989-01-01

Approximate analytical formulas have been derived for the transformation of Legendre coefficients of double-differential continuum cross sections of two-body nuclear reactions from the center-of-mass to the laboratory system. This transformation differs from that of elastic-scattering angular distribution coefficients on its accuracy which depends not only upon the target mass, but also upon outgoing energies. A fast code has been written to transform Legendre coefficients of neutron inelastic scattering cross-sections. The calculations have been carried out using a recently introduced numerical integration method for more complicated problems in which the energy spectrum is either an evaporation spectrum or a spectrum obtained from a (pre-)compound model. The results are quite satisfactory provided that the target mass or the outgoing energy is not sufficiently low

Application of the Fourier pseudospectral time-domain method in orthogonal curvilinear coordinates for near-rigid moderately curved surfaces.

Science.gov (United States)

Hornikx, Maarten; Dragna, Didier

2015-07-01

The Fourier pseudospectral time-domain method is an efficient wave-based method to model sound propagation in inhomogeneous media. One of the limitations of the method for atmospheric sound propagation purposes is its restriction to a Cartesian grid, confining it to staircase-like geometries. A transform from the physical coordinate system to the curvilinear coordinate system has been applied to solve more arbitrary geometries. For applicability of this method near the boundaries, the acoustic velocity variables are solved for their curvilinear components. The performance of the curvilinear Fourier pseudospectral method is investigated in free field and for outdoor sound propagation over an impedance strip for various types of shapes. Accuracy is shown to be related to the maximum grid stretching ratio and deformation of the boundary shape and computational efficiency is reduced relative to the smallest grid cell in the physical domain. The applicability of the curvilinear Fourier pseudospectral time-domain method is demonstrated by investigating the effect of sound propagation over a hill in a nocturnal boundary layer. With the proposed method, accurate and efficient results for sound propagation over smoothly varying ground surfaces with high impedances can be obtained.

Quadratic Lagrangians and Legendre transformation

International Nuclear Information System (INIS)

Magnano, G.

1988-01-01

In recent years interest is grown about the so-called non-linear Lagrangians for gravitation. In particular, the quadratic lagrangians are currently believed to play a fundamental role both for quantum gravity and for the super-gravity approach. The higher order and high degree of non-linearity of these theories make very difficult to extract physical information out of them. The author discusses how the Legendre transformation can be applied to a wide class of non-linear theories: it corresponds to a conformal transformation whenever the Lagrangian depends only on the scalar curvature, while it has a more general form if the Lagrangian depends on the full Ricci tensor

Numerical solution of sixth-order boundary-value problems using Legendre wavelet collocation method

Science.gov (United States)

Sohaib, Muhammad; Haq, Sirajul; Mukhtar, Safyan; Khan, Imad

2018-03-01

An efficient method is proposed to approximate sixth order boundary value problems. The proposed method is based on Legendre wavelet in which Legendre polynomial is used. The mechanism of the method is to use collocation points that converts the differential equation into a system of algebraic equations. For validation two test problems are discussed. The results obtained from proposed method are quite accurate, also close to exact solution, and other different methods. The proposed method is computationally more effective and leads to more accurate results as compared to other methods from literature.

Application of Legendre spectral-collocation method to delay differential and stochastic delay differential equation

Science.gov (United States)

Khan, Sami Ullah; Ali, Ishtiaq

2018-03-01

Explicit solutions to delay differential equation (DDE) and stochastic delay differential equation (SDDE) can rarely be obtained, therefore numerical methods are adopted to solve these DDE and SDDE. While on the other hand due to unstable nature of both DDE and SDDE numerical solutions are also not straight forward and required more attention. In this study, we derive an efficient numerical scheme for DDE and SDDE based on Legendre spectral-collocation method, which proved to be numerical methods that can significantly speed up the computation. The method transforms the given differential equation into a matrix equation by means of Legendre collocation points which correspond to a system of algebraic equations with unknown Legendre coefficients. The efficiency of the proposed method is confirmed by some numerical examples. We found that our numerical technique has a very good agreement with other methods with less computational effort.

N-Level Quantum Systems and Legendre Functions

OpenAIRE

Mazurenko, A. S.; Savva, V. A.

2001-01-01

An excitation dynamics of new quantum systems of N equidistant energy levels in a monochromatic field has been investigated. To obtain exact analytical solutions of dynamic equations an analytical method based on orthogonal functions of a real argument has been proposed. Using the orthogonal Legendre functions we have found an exact analytical expression for a population probability amplitude of the level n. Various initial conditions for the excitation of N-level quantum systems have been co...

The application of Legendre-tau approximation to parameter identification for delay and partial differential equations

Science.gov (United States)

Ito, K.

1983-01-01

Approximation schemes based on Legendre-tau approximation are developed for application to parameter identification problem for delay and partial differential equations. The tau method is based on representing the approximate solution as a truncated series of orthonormal functions. The characteristic feature of the Legendre-tau approach is that when the solution to a problem is infinitely differentiable, the rate of convergence is faster than any finite power of 1/N; higher accuracy is thus achieved, making the approach suitable for small N.

Experimental analysis of shape deformation of evaporating droplet using Legendre polynomials

Energy Technology Data Exchange (ETDEWEB)

Sanyal, Apratim [Department of Mechanical Engineering, Indian Institute of Science, Bangalore 560012 (India); Basu, Saptarshi, E-mail: sbasu@mecheng.iisc.ernet.in [Department of Mechanical Engineering, Indian Institute of Science, Bangalore 560012 (India); Kumar, Ranganathan [Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816 (United States)

2014-01-24

Experiments involving heating of liquid droplets which are acoustically levitated, reveal specific modes of oscillations. For a given radiation flux, certain fluid droplets undergo distortion leading to catastrophic bag type breakup. The voltage of the acoustic levitator has been kept constant to operate at a nominal acoustic pressure intensity, throughout the experiments. Thus the droplet shape instabilities are primarily a consequence of droplet heating through vapor pressure, surface tension and viscosity. A novel approach is used by employing Legendre polynomials for the mode shape approximation to describe the thermally induced instabilities. The two dominant Legendre modes essentially reflect (a) the droplet size reduction due to evaporation, and (b) the deformation around the equilibrium shape. Dissipation and inter-coupling of modal energy lead to stable droplet shape while accumulation of the same ultimately results in droplet breakup.

Experimental analysis of shape deformation of evaporating droplet using Legendre polynomials

International Nuclear Information System (INIS)

Sanyal, Apratim; Basu, Saptarshi; Kumar, Ranganathan

2014-01-01

Experiments involving heating of liquid droplets which are acoustically levitated, reveal specific modes of oscillations. For a given radiation flux, certain fluid droplets undergo distortion leading to catastrophic bag type breakup. The voltage of the acoustic levitator has been kept constant to operate at a nominal acoustic pressure intensity, throughout the experiments. Thus the droplet shape instabilities are primarily a consequence of droplet heating through vapor pressure, surface tension and viscosity. A novel approach is used by employing Legendre polynomials for the mode shape approximation to describe the thermally induced instabilities. The two dominant Legendre modes essentially reflect (a) the droplet size reduction due to evaporation, and (b) the deformation around the equilibrium shape. Dissipation and inter-coupling of modal energy lead to stable droplet shape while accumulation of the same ultimately results in droplet breakup.

On the derivative of the Legendre function of the first kind with respect to its degree

International Nuclear Information System (INIS)

Szmytkowski, Radoslaw

2006-01-01

We study the derivative of the Legendre function of the first kind, P ν (z), with respect to its degree ν. At first, we provide two contour integral representations for ∂P ν (z)/∂ν. Then, we proceed to investigate the case of [∂P ν (z)/∂ν] ν=n , with n being an integer; this case is met in some physical and engineering problems. Since it holds that [∂P ν' (z)/∂ν'] ν'==ν-1 -[∂P ν' (z0/∂ν'] ν'=ν , we focus on the sub-case of n being a non-negative integer. We show that ∂P ν (z)/∂ν vertical bar ν=n = P n (z) ln((z+1)/2) + R n (z) (n element of N) where R n (z) is a polynomial in z of degree n. We present alternative derivations of several known explicit expressions for R n (z) and also add some new. A generating function for R n (z) is also constructed. Properties of the polynomials V n (z) = [R n (z) + (-1) n R n (-z)]/2 and W n-1 (z) = -[R n (z) - (-1) n R n (-z)]/2 are also investigated. It is found that W n-1 (z) is the Christoffel polynomial, well known from the theory of the Legendre function of the second kind, Q n (z). As examples of applications of the results obtained, we present non-standard derivations of some representations of Q n (z), sum to closed forms some Legendre series, evaluate some definite integrals involving Legendre polynomials and also derive an explicit representation of the indefinite integral of the Legendre polynomial squared

A Fast, Simple, and Stable Chebyshev--Legendre Transform Using an Asymptotic Formula

KAUST Repository

Hale, Nicholas; Townsend, Alex

2014-01-01

-known asymptotic formula for Legendre polynomials of large degree as a weighted linear combination of Chebyshev polynomials, which can then be evaluated by using the discrete cosine transform. Numerical results are provided to demonstrate the efficiency

A new representation for ground states and its Legendre transforms

International Nuclear Information System (INIS)

Cedillo, A.

1994-01-01

The ground-state energy of an electronic system is a functional of the number of electrons (N) and the external potential (v): E = E(N,V), this is the energy representation for ground states. In 1982, Nalewajski defined the Legendre transforms of this representation, taking advantage of the strict concavity of E with respect to their variables (concave respect v and convex respect N), and he also constructed a scheme for the reduction of derivatives of his representations. Unfortunately, N and the electronic density (p) were the independent variables of one of these representations, but p depends explicitly on N. In this work, this problem is avoided using the energy per particle (ε) as the basic variables, and the Legendre transformations can be defined. A procedure for the reduction of derivatives is generated for the new four representations and, in contrast to the Nalewajski's procedure, it only includes derivatives of the four representations. Finally, the reduction of derivatives is used to test some relationships between the hardness and softness kernels

Development of pattern recognition algorithms for the central drift chamber of the Belle II detector

Energy Technology Data Exchange (ETDEWEB)

Trusov, Viktor

2016-11-04

In this thesis, the development of one of the pattern recognition algorithms for the Belle II experiment based on conformal and Legendre transformations is presented. In order to optimize the performance of the algorithm (CPU time and efficiency) specialized processing steps have been introduced. To show achieved results, Monte-Carlo based efficiency measurements of the tracking algorithms in the Central Drift Chamber (CDC) has been done.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

Directory of Open Access Journals (Sweden)

Maria Gabriela Campolina Diniz Peixoto

2014-05-01

Full Text Available The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524 of test-day milk yield (TDMY from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects, whereas the contemporary group, calving age (linear and quadratic effects and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Generalizations of an integral for Legendre polynomials by Persson and Strang

NARCIS (Netherlands)

Diekema, E.; Koornwinder, T.H.

2012-01-01

Persson and Strang (2003) evaluated the integral over [−1,1] of a squared odd degree Legendre polynomial divided by x2 as being equal to 2. We consider a similar integral for orthogonal polynomials with respect to a general even orthogonality measure, with Gegenbauer and Hermite polynomials as

Modified rational Legendre approach to laminar viscous flow over a semi-infinite flat plate

International Nuclear Information System (INIS)

Tajvidi, T.; Razzaghi, M.; Dehghan, M.

2008-01-01

A numerical method for solving the classical Blasius' equation is proposed. The Blasius' equation is a third order nonlinear ordinary differential equation , which arises in the problem of the two-dimensional laminar viscous flow over a semi-infinite flat plane. The approach is based on a modified rational Legendre tau method. The operational matrices for the derivative and product of the modified rational Legendre functions are presented. These matrices together with the tau method are utilized to reduce the solution of Blasius' equation to the solution of a system of algebraic equations. A numerical evaluation is included to demonstrate the validity and applicability of the method and a comparison is made with existing results

A new Fortran 90 program to compute regular and irregular associated Legendre functions (new version announcement)

Science.gov (United States)

Schneider, Barry I.; Segura, Javier; Gil, Amparo; Guan, Xiaoxu; Bartschat, Klaus

2018-04-01

This is a revised and updated version of a modern Fortran 90 code to compute the regular Plm (x) and irregular Qlm (x) associated Legendre functions for all x ∈(- 1 , + 1) (on the cut) and | x | > 1 and integer degree (l) and order (m). The necessity to revise the code comes as a consequence of some comments of Prof. James Bremer of the UC//Davis Mathematics Department, who discovered that there were errors in the code for large integer degree and order for the normalized regular Legendre functions on the cut.

Pseudospectral operational matrix for numerical solution of single and multiterm time fractional diffusion equation

OpenAIRE

GHOLAMI, SAEID; BABOLIAN, ESMAIL; JAVIDI, MOHAMMAD

2016-01-01

This paper presents a new numerical approach to solve single and multiterm time fractional diffusion equations. In this work, the space dimension is discretized to the Gauss$-$Lobatto points. We use the normalized Grunwald approximation for the time dimension and a pseudospectral successive integration matrix for the space dimension. This approach shows that with fewer numbers of points, we can approximate the solution with more accuracy. Some examples with numerical results in tables and fig...

Finger crease pattern recognition using Legendre moments and principal component analysis

Science.gov (United States)

Luo, Rongfang; Lin, Tusheng

2007-03-01

The finger joint lines defined as finger creases and its distribution can identify a person. In this paper, we propose a new finger crease pattern recognition method based on Legendre moments and principal component analysis (PCA). After obtaining the region of interest (ROI) for each finger image in the pre-processing stage, Legendre moments under Radon transform are applied to construct a moment feature matrix from the ROI, which greatly decreases the dimensionality of ROI and can represent principal components of the finger creases quite well. Then, an approach to finger crease pattern recognition is designed based on Karhunen-Loeve (K-L) transform. The method applies PCA to a moment feature matrix rather than the original image matrix to achieve the feature vector. The proposed method has been tested on a database of 824 images from 103 individuals using the nearest neighbor classifier. The accuracy up to 98.584% has been obtained when using 4 samples per class for training. The experimental results demonstrate that our proposed approach is feasible and effective in biometrics.

De la glosa a la publicidad. Notas para una lectura de Pierre Legendre

Directory of Open Access Journals (Sweden)

Bellido, José

2008-12-01

Full Text Available By emphasizing the singular experience of the act of reading, this paper presents the work of a French legal philosopher and psychoanalyst: Pierre Legendre. Whereas this attempt could be simultaneously an impossible and irritating venture, its aim is to emphasize something that is not so often seen in legal theory: an inquiry into the nuances of the legal unconscious. In doing so, the paper opens with some references to his particular understanding of love and the spectacular as a legal resource to dominate its subjects. It continues to be peppered with several attractive spaces in which Legendre’s ecounters the binding force in the imaginary of the legal institution.

Señalando la experiencia singular del acto de leer, este trabajo presenta la obra de un filósofo del derecho y psicoanalista francés: Pierre Legendre. A pesar de que tal proyecto pudiera constituir una empresa tan imposible como irritante, el propósito principal es resaltar un elemento que no suele observarse con frecuencia en la teoría del derecho: un recorrido por los diversos matices del inconsciente jurídico. El trabajo comienza con algunas referencias a su concepción particular del amor y del espectáculo como recursos legales para dominar a los sujetos. Y continúa con algunos espacios sugerentes donde Legendre encuentra la fuerza vinculante en el imaginario de la institución jurídica.

Pseudospectral collocation methods for fourth order differential equations

Science.gov (United States)

Malek, Alaeddin; Phillips, Timothy N.

1994-01-01

Collocation schemes are presented for solving linear fourth order differential equations in one and two dimensions. The variational formulation of the model fourth order problem is discretized by approximating the integrals by a Gaussian quadrature rule generalized to include the values of the derivative of the integrand at the boundary points. Collocation schemes are derived which are equivalent to this discrete variational problem. An efficient preconditioner based on a low-order finite difference approximation to the same differential operator is presented. The corresponding multidomain problem is also considered and interface conditions are derived. Pseudospectral approximations which are C1 continuous at the interfaces are used in each subdomain to approximate the solution. The approximations are also shown to be C3 continuous at the interfaces asymptotically. A complete analysis of the collocation scheme for the multidomain problem is provided. The extension of the method to the biharmonic equation in two dimensions is discussed and results are presented for a problem defined in a nonrectangular domain.

Legendre Duality of Spherical and Gaussian Spin Glasses

Energy Technology Data Exchange (ETDEWEB)

Genovese, Giuseppe, E-mail: giuseppe.genovese@math.uzh.ch [Universität Zürich, Institut für Mathematik (Switzerland); Tantari, Daniele, E-mail: daniele.tantari@sns.it [Scuola Normale Superiore di Pisa, Centro Ennio de Giorgi (Italy)

2015-12-15

The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model.

Legendre Duality of Spherical and Gaussian Spin Glasses

International Nuclear Information System (INIS)

Genovese, Giuseppe; Tantari, Daniele

2015-01-01

The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model

Pseudospectral modeling and dispersion analysis of Rayleigh waves in viscoelastic media

Science.gov (United States)

Zhang, K.; Luo, Y.; Xia, J.; Chen, C.

2011-01-01

Multichannel Analysis of Surface Waves (MASW) is one of the most widely used techniques in environmental and engineering geophysics to determine shear-wave velocities and dynamic properties, which is based on the elastic layered system theory. Wave propagation in the Earth, however, has been recognized as viscoelastic and the propagation of Rayleigh waves presents substantial differences in viscoelastic media as compared with elastic media. Therefore, it is necessary to carry out numerical simulation and dispersion analysis of Rayleigh waves in viscoelastic media to better understand Rayleigh-wave behaviors in the real world. We apply a pseudospectral method to the calculation of the spatial derivatives using a Chebyshev difference operator in the vertical direction and a Fourier difference operator in the horizontal direction based on the velocity-stress elastodynamic equations and relations of linear viscoelastic solids. This approach stretches the spatial discrete grid to have a minimum grid size near the free surface so that high accuracy and resolution are achieved at the free surface, which allows an effective incorporation of the free surface boundary conditions since the Chebyshev method is nonperiodic. We first use an elastic homogeneous half-space model to demonstrate the accuracy of the pseudospectral method comparing with the analytical solution, and verify the correctness of the numerical modeling results for a viscoelastic half-space comparing the phase velocities of Rayleigh wave between the theoretical values and the dispersive image generated by high-resolution linear Radon transform. We then simulate three types of two-layer models to analyze dispersive-energy characteristics for near-surface applications. Results demonstrate that the phase velocity of Rayleigh waves in viscoelastic media is relatively higher than in elastic media and the fundamental mode increases by 10-16% when the frequency is above 10. Hz due to the velocity dispersion of P

Characterizing the Lyα forest flux probability distribution function using Legendre polynomials

Energy Technology Data Exchange (ETDEWEB)

Cieplak, Agnieszka M.; Slosar, Anže, E-mail: acieplak@bnl.gov, E-mail: anze@bnl.gov [Brookhaven National Laboratory, Bldg 510, Upton, NY, 11973 (United States)

2017-10-01

The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n -th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. We find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.

Characterizing the Lyα forest flux probability distribution function using Legendre polynomials

Science.gov (United States)

Cieplak, Agnieszka M.; Slosar, Anže

2017-10-01

The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n-th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. We find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.

An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

KAUST Repository

Zhan, Ge

2013-02-19

The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward-backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations. © 2013 Sinopec Geophysical Research Institute.

An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

International Nuclear Information System (INIS)

Zhan, Ge; Pestana, Reynam C; Stoffa, Paul L

2013-01-01

The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward–backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations. (paper)

Nonlinear Legendre Spectral Finite Elements for Wind Turbine Blade Dynamics: Preprint

Energy Technology Data Exchange (ETDEWEB)

Wang, Q.; Sprague, M. A.; Jonkman, J.; Johnson, N.

2014-01-01

This paper presents a numerical implementation and examination of new wind turbine blade finite element model based on Geometrically Exact Beam Theory (GEBT) and a high-order spectral finite element method. The displacement-based GEBT is presented, which includes the coupling effects that exist in composite structures and geometric nonlinearity. Legendre spectral finite elements (LSFEs) are high-order finite elements with nodes located at the Gauss-Legendre-Lobatto points. LSFEs can be an order of magnitude more efficient that low-order finite elements for a given accuracy level. Interpolation of the three-dimensional rotation, a major technical barrier in large-deformation simulation, is discussed in the context of LSFEs. It is shown, by numerical example, that the high-order LSFEs, where weak forms are evaluated with nodal quadrature, do not suffer from a drawback that exists in low-order finite elements where the tangent-stiffness matrix is calculated at the Gauss points. Finally, the new LSFE code is implemented in the new FAST Modularization Framework for dynamic simulation of highly flexible composite-material wind turbine blades. The framework allows for fully interactive simulations of turbine blades in operating conditions. Numerical examples showing validation and LSFE performance will be provided in the final paper.

Using Legendre Functions for Spatial Covariance Approximation and Investigation of Radial Nonisotrophy for NOGAPS Data

National Research Council Canada - National Science Library

Franke, Richard

2001-01-01

.... It was found that for all levels the approximation of the covariance data for pressure height innovations by Legendre functions led to positive coefficients for up to 25 terms except at the some low and high levels...

Noniterative accurate algorithm for the exact exchange potential of density-functional theory

International Nuclear Information System (INIS)

Cinal, M.; Holas, A.

2007-01-01

An algorithm for determination of the exchange potential is constructed and tested. It represents a one-step procedure based on the equations derived by Krieger, Li, and Iafrate (KLI) [Phys. Rev. A 46, 5453 (1992)], implemented already as an iterative procedure by Kuemmel and Perdew [Phys. Rev. Lett. 90, 043004 (2003)]. Due to suitable transformation of the KLI equations, we can solve them avoiding iterations. Our algorithm is applied to the closed-shell atoms, from Be up to Kr, within the DFT exchange-only approximation. Using pseudospectral techniques for representing orbitals, we obtain extremely accurate values of total and orbital energies with errors at least four orders of magnitude smaller than known in the literature

Characterizing the Lyman-alpha forest flux probability distribution function using Legendre polynomials

Science.gov (United States)

Cieplak, Agnieszka; Slosar, Anze

2018-01-01

The Lyman-alpha forest has become a powerful cosmological probe at intermediate redshift. It is a highly non-linear field with much information present beyond the power spectrum. The flux probability flux distribution (PDF) in particular has been a successful probe of small scale physics. However, it is also sensitive to pixel noise, spectrum resolution, and continuum fitting, all of which lead to possible biased estimators. Here we argue that measuring the coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. Since the n-th Legendre coefficient can be expressed as a linear combination of the first n moments of the field, this allows for the coefficients to be measured in the presence of noise and allows for a clear route towards marginalization over the mean flux. Additionally, in the presence of noise, a finite number of these coefficients are well measured with a very sharp transition into noise dominance. This compresses the information into a small amount of well-measured quantities. Finally, we find that measuring fewer quasars with high signal-to-noise produces a higher amount of recoverable information.

Convexity Conditions and the Legendre-Fenchel Transform for the Product of Finitely Many Positive Definite Quadratic Forms

International Nuclear Information System (INIS)

Zhao Yunbin

2010-01-01

While the product of finitely many convex functions has been investigated in the field of global optimization, some fundamental issues such as the convexity condition and the Legendre-Fenchel transform for the product function remain unresolved. Focusing on quadratic forms, this paper is aimed at addressing the question: When is the product of finitely many positive definite quadratic forms convex, and what is the Legendre-Fenchel transform for it? First, we show that the convexity of the product is determined intrinsically by the condition number of so-called 'scaled matrices' associated with quadratic forms involved. The main result claims that if the condition number of these scaled matrices are bounded above by an explicit constant (which depends only on the number of quadratic forms involved), then the product function is convex. Second, we prove that the Legendre-Fenchel transform for the product of positive definite quadratic forms can be expressed, and the computation of the transform amounts to finding the solution to a system of equations (or equally, finding a Brouwer's fixed point of a mapping) with a special structure. Thus, a broader question than the open 'Question 11' in Hiriart-Urruty (SIAM Rev. 49, 225-273, 2007) is addressed in this paper.

Representation of the Fokker-Planck collision term for Coulomb interaction as series of Legendre polynomials

International Nuclear Information System (INIS)

Almeida Ferreira, A.C. de.

1984-01-01

For problems with azimuthal symmetry in velocity space, the distribution function depends only on the speed and on the pitch angle. The angular dependence of the distribution function is expanded in Legendre polynomials, and the expansions of the collision integrals describing two-body Coulomb interactions in a plasma are determined through the use of the Rosenbluth potentials. The electron distribution function is written as a Maxwellian plus a deviation, and the representation in Legendre polynomials of the electron-electron collision term is given for both its linear and nonlinear part. To determine the representation of the electron-ion collision term it is assumed that the ion distribution is much narrower in velocity space than the electron distribution, and shifted from the origin by a flow velocity. The equations are presented in a form that is suitable for their use in a computer. (Author) [pt

PSpectRe: a pseudo-spectral code for (P)reheating

International Nuclear Information System (INIS)

Easther, Richard; Finkel, Hal; Roth, Nathaniel

2010-01-01

PSpectRe is a C++ program that uses Fourier-space pseudo-spectral methods to evolve interacting scalar fields in an expanding universe. PSpectRe is optimized for the analysis of parametric resonance in the post-inflationary universe and provides an alternative to finite differencing codes, such as Defrost and LatticeEasy. PSpectRe has both second- (Velocity-Verlet) and fourth-order (Runge-Kutta) time integrators. Given the same number of spatial points and/or momentum modes, PSpectRe is not significantly slower than finite differencing codes, despite the need for multiple Fourier transforms at each timestep, and exhibits excellent energy conservation. Further, by computing the post-resonance equation of state, we show that in some circumstances PSpectRe obtains reliable results while using substantially fewer points than a finite differencing code. PSpectRe is designed to be easily extended to other problems in early-universe cosmology, including the generation of gravitational waves during phase transitions and pre-inflationary bubble collisions. Specific applications of this code will be described in future work

An hp symplectic pseudospectral method for nonlinear optimal control

Science.gov (United States)

Peng, Haijun; Wang, Xinwei; Li, Mingwu; Chen, Biaosong

2017-01-01

An adaptive symplectic pseudospectral method based on the dual variational principle is proposed and is successfully applied to solving nonlinear optimal control problems in this paper. The proposed method satisfies the first order necessary conditions of continuous optimal control problems, also the symplectic property of the original continuous Hamiltonian system is preserved. The original optimal control problem is transferred into a set of nonlinear equations which can be solved easily by Newton-Raphson iterations, and the Jacobian matrix is found to be sparse and symmetric. The proposed method, on one hand, exhibits exponent convergence rates when the number of collocation points are increasing with the fixed number of sub-intervals; on the other hand, exhibits linear convergence rates when the number of sub-intervals is increasing with the fixed number of collocation points. Furthermore, combining with the hp method based on the residual error of dynamic constraints, the proposed method can achieve given precisions in a few iterations. Five examples highlight the high precision and high computational efficiency of the proposed method.

Solution of volume-surface integral equations using higher-order hierarchical Legendre basis functions

DEFF Research Database (Denmark)

Kim, Oleksiy S.; Meincke, Peter; Breinbjerg, Olav

2007-01-01

The problem of electromagnetic scattering by composite metallic and dielectric objects is solved using the coupled volume-surface integral equation (VSIE). The method of moments (MoM) based on higher-order hierarchical Legendre basis functions and higher-order curvilinear geometrical elements...... with the analytical Mie series solution. Scattering by more complex metal-dielectric objects are also considered to compare the presented technique with other numerical methods....

Time-splitting combined with exponential wave integrator fourier pseudospectral method for Schrödinger-Boussinesq system

Science.gov (United States)

Liao, Feng; Zhang, Luming; Wang, Shanshan

2018-02-01

In this article, we formulate an efficient and accurate numerical method for approximations of the coupled Schrödinger-Boussinesq (SBq) system. The main features of our method are based on: (i) the applications of a time-splitting Fourier spectral method for Schrödinger-like equation in SBq system, (ii) the utilizations of exponential wave integrator Fourier pseudospectral for spatial derivatives in the Boussinesq-like equation. The scheme is fully explicit and efficient due to fast Fourier transform. The numerical examples are presented to show the efficiency and accuracy of our method.

Costate Estimation of PMP-Based Control Strategy for PHEV Using Legendre Pseudospectral Method

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Hanbing Wei

2016-01-01

Full Text Available Costate value plays a significant role in the application of PMP-based control strategy for PHEV. It is critical for terminal SOC of battery at destination and corresponding equivalent fuel consumption. However, it is not convenient to choose the approximate costate in real driving condition. In the paper, the optimal control problem of PHEV based on PMP has been converted to nonlinear programming problem. By means of KKT condition costate can be approximated as KKT multipliers of NLP divided by the LGL weights. A kind of general costate estimation approach is proposed for predefined driving condition in this way. Dynamic model has been established in Matlab/Simulink in order to prove the effectiveness of the method. Simulation results demonstrate that the method presented in the paper can deduce the closer value of global optimal value than constant initial costate value. This approach can be used for initial costate and jump condition estimation of PMP-based control strategy for PHEV.

A Novel Radiation Transport Algorithm for Radiography Simulations

International Nuclear Information System (INIS)

Inanc, Feyzi

2004-01-01

The simulations used in the NDE community are becoming more realistic with the introduction of more physics. In this work, we have developed a new algorithm that is capable of representing photon and charged particle fluxes through spherical harmonic expansions in a manner similar to well known discrete ordinates method with the exception that Boltzmann operator is treated through exact integration rather than conventional Legendre expansions. This approach provides a mean to include radiation interactions for higher energy regimes where there are additional physical mechanisms for photons and charged particles

Simulation of seismograms in a 2-D viscoelastic Earth by pseudospectral methods

Energy Technology Data Exchange (ETDEWEB)

Carcione, Jose M [Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS), Trieste (Italy); Helle, Hans B [Norsk Hydro a.s., 0 and E Research Centre, Bergen (Norway); Seriani, Geza [Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS), Trieste (Italy); Plasencia Linares, Milton P [Facultad de Ciencias Astronomicas y Geofisicas, Universidad Nacional de La Plata, La Plata (Argentina)

2005-04-15

Using an improved global pseudospectral modeling algorithm we synthesize seismograms generated by oceanic and continental earthquakes. Attention is given to attenuation, to explicit modeling of boundary conditions at the ocean-bottom interface, simulation of the Rayleigh window and interface-wave propagation. The algorithm is based on Fourier and Chebyshev differential operators and a domain-decomposition technique - one grid for the fluid and another grid for the solid. Wave propagation in the oceanic and continent crusts and mantle is modeled by using a viscoelastic stress-strain relation based on memory variables. The main physical phenomena associated with an ocean-crust system are modeled, including Scholte waves, leaking Rayleigh waves, dispersive modes, and the Rayleigh-window phenomenon due to a minimum in the reflection coefficient of the ocean bottom, which has not been simulated with direct methods. In particular, we model Rayleigh modes (mainly the M11 mode), and coupled Rayleigh-Scholte waves, for which the dispersion relation is solved in simple cases. Also, we model the effects of random. [Spanish] El algoritmo de modulacion seudoespectral es mejorado y aplicado a la simulacion de sismogramas generados por sismos oceanicos y continentales, como atencion a la atenuacion y a la modelacion explicita de condiciones a la frontera en el fondo oceanico y a la simulacion de la ventana de Rayleigh y la propagacion en interfases. El algoritmo se basa en los operadores diferenciales de Fourier y de Chebyshev con una tecnica de decomposicion de dominios, una malla para el fluido y otra para el solido. Para la propagacion se usa una relacion de esfuerzo-deformacion basada en variables de memoria. Entre los fenomenos modelados se incluyen las ondas de Scholte, las ondas evanescentes de Rayleigh y los modos dispersivos, asi como la ventana de Rayleigh, un minimo del coeficiente de reflexion en el fondo oceanico que nunca ha sido simulado con metodos directos. Hemos

Fitting of two and three variant polynomials from experimental data through the least squares method. (Using of the codes AJUS-2D, AJUS-3D and LEGENDRE-2D); Ajuste de polinomios en dos y tres variables independientes por el metodo de minimos cuadrados. (Desarrollo de los codigos AJUS-2D, AJUS-3D y LEGENDRE-2D)

Energy Technology Data Exchange (ETDEWEB)

Sanchez Miro, J J; Sanz Martin, J C

1994-07-01

Obtaining polynomial fittings from observational data in two and three dimensions is an interesting and practical task. Such an arduous problem suggests the development of an automatic code. The main novelty we provide lies in the generalization of the classical least squares method in three FORTRAN 77 programs usable in any sampling problem. Furthermore, we introduce the orthogonal 2D-Legendre function in the fitting process. These FORTRAN 77 programs are equipped with the options to calculate the approximation quality standard indicators, obviously generalized to two and three dimensions (correlation nonlinear factor, confidence intervals, cuadratic mean error, and so on). The aim of this paper is to rectify the absence of fitting algorithms for more than one independent variable in mathematical libraries. (Author) 10 refs.

Modified Legendre Wavelets Technique for Fractional Oscillation Equations

Directory of Open Access Journals (Sweden)

Syed Tauseef Mohyud-Din

2015-10-01

Full Text Available Physical Phenomena’s located around us are primarily nonlinear in nature and their solutions are of highest significance for scientists and engineers. In order to have a better representation of these physical models, fractional calculus is used. Fractional order oscillation equations are included among these nonlinear phenomena’s. To tackle with the nonlinearity arising, in these phenomena’s we recommend a new method. In the proposed method, Picard’s iteration is used to convert the nonlinear fractional order oscillation equation into a fractional order recurrence relation and then Legendre wavelets method is applied on the converted problem. In order to check the efficiency and accuracy of the suggested modification, we have considered three problems namely: fractional order force-free Duffing–van der Pol oscillator, forced Duffing–van der Pol oscillator and higher order fractional Duffing equations. The obtained results are compared with the results obtained via other techniques.

Legendre-tau approximation for functional differential equations. II - The linear quadratic optimal control problem

Science.gov (United States)

Ito, Kazufumi; Teglas, Russell

1987-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

A multidomain chebyshev pseudo-spectral method for fluid flow and heat transfer from square cylinders

KAUST Repository

Wang, Zhiheng

2015-01-01

A simple multidomain Chebyshev pseudo-spectral method is developed for two-dimensional fluid flow and heat transfer over square cylinders. The incompressible Navier-Stokes equations with primitive variables are discretized in several subdomains of the computational domain. The velocities and pressure are discretized with the same order of Chebyshev polynomials, i.e., the PN-PN method. The Projection method is applied in coupling the pressure with the velocity. The present method is first validated by benchmark problems of natural convection in a square cavity. Then the method based on multidomains is applied to simulate fluid flow and heat transfer from square cylinders. The numerical results agree well with the existing results. © Taylor & Francis Group, LLC.

Study of a method to solve the one speed, three dimensional transport equation using the finite element method and the associated Legendre function

International Nuclear Information System (INIS)

Fernandes, A.

1991-01-01

A method to solve three dimensional neutron transport equation and it is based on the original work suggested by J.K. Fletcher (42, 43). The angular dependence of the flux is approximated by associated Legendre functions and the finite element method is applied to the space components is presented. When the angular flux, the scattering cross section and the neutrons source are expanded in associated Legendre functions, the first order neutron transport equation is reduced to a coupled set of second order diffusion like equations. These equations are solved in an iterative way by the finite element method to the moments. (author)

Legendre condition and the stabilization problem for classical soliton solutions in generalized Skyrme models

International Nuclear Information System (INIS)

Kiknadze, N.A.; Khelashvili, A.A.

1990-01-01

The problem on stability of classical soliton solutions is studied from the unique point of view: the Legendre condition - necessary condition of existence of weak local minimum for energy functional (term soliton is used here in the wide sense) is used. Limits to parameters of the model Lagrangians are obtained; it is shown that there is no soliton stabilization in some of them despite the phenomenological achievements. The Jacoby sufficient condition is discussed

Bound-preserving Legendre-WENO finite volume schemes using nonlinear mapping

Science.gov (United States)

Smith, Timothy; Pantano, Carlos

2017-11-01

We present a new method to enforce field bounds in high-order Legendre-WENO finite volume schemes. The strategy consists of reconstructing each field through an intermediate mapping, which by design satisfies realizability constraints. Determination of the coefficients of the polynomial reconstruction involves nonlinear equations that are solved using Newton's method. The selection between the original or mapped reconstruction is implemented dynamically to minimize computational cost. The method has also been generalized to fields that exhibit interdependencies, requiring multi-dimensional mappings. Further, the method does not depend on the existence of a numerical flux function. We will discuss details of the proposed scheme and show results for systems in conservation and non-conservation form. This work was funded by the NSF under Grant DMS 1318161.

Adapting a Fourier pseudospectral method to Dirichlet boundary conditions for Rayleigh-Bénard convection

Directory of Open Access Journals (Sweden)

I. C. Ramos

2015-10-01

Full Text Available We present the adaptation to non-free boundary conditions of a pseudospectral method based on the (complex Fourier transform. The method is applied to the numerical integration of the Oberbeck-Boussinesq equations in a Rayleigh-Bénard cell with no-slip boundary conditions for velocity and Dirichlet boundary conditions for temperature. We show the first results of a 2D numerical simulation of dry air convection at high Rayleigh number (. These results are the basis for the later study, by the same method, of wet convection in a solar still. Received: 20 Novembre 2014, Accepted: 15 September 2015; Edited by: C. A. Condat, G. J. Sibona; DOI:http://dx.doi.org/10.4279/PIP.070015 Cite as: I C Ramos, C B Briozzo, Papers in Physics 7, 070015 (2015

Legendre-tau approximation for functional differential equations. Part 2: The linear quadratic optimal control problem

Science.gov (United States)

Ito, K.; Teglas, R.

1984-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

A conservative Fourier pseudospectral algorithm for a coupled nonlinear Schrödinger system

International Nuclear Information System (INIS)

Cai Jia-Xiang; Wang Yu-Shun

2013-01-01

We derive a new method for a coupled nonlinear Schrödinger system by using the square of first-order Fourier spectral differentiation matrix D 1 instead of traditional second-order Fourier spectral differentiation matrix D 2 to approximate the second derivative. We prove the proposed method preserves the charge and energy conservation laws exactly. In numerical tests, we display the accuracy of numerical solution and the role of the nonlinear coupling parameter in cases of soliton collisions. Numerical experiments also exhibit the excellent performance of the method in preserving the charge and energy conservation laws. These numerical results verify that the proposed method is both a charge-preserving and an energy-preserving algorithm

Fitting of two and three variant polynomials from experimental data through the least squares method. (Using of the codes AJUS-2D, AJUS-3D and LEGENDRE-2D)

International Nuclear Information System (INIS)

Sanchez Miro, J. J.; Sanz Martin, J. C.

1994-01-01

Obtaining polynomial fittings from observational data in two and three dimensions is an interesting and practical task. Such an arduous problem suggests the development of an automatic code. The main novelty we provide lies in the generalization of the classical least squares method in three FORTRAN 77 programs usable in any sampling problem. Furthermore, we introduce the orthogonal 2D-Legendre function in the fitting process. These FORTRAN 77 programs are equipped with the options to calculate the approximation quality standard indicators, obviously generalized to two and three dimensions (correlation nonlinear factor, confidence intervals, cuadratic mean error, and so on). The aim of this paper is to rectify the absence of fitting algorithms for more than one independent variable in mathematical libraries. (Author) 10 refs

A hybrid radial basis function-pseudospectral method for thermal convection in a 3-D spherical shell

KAUST Repository

Wright, G. B.

2010-07-01

A novel hybrid spectral method that combines radial basis function (RBF) and Chebyshev pseudospectral methods in a "2 + 1" approach is presented for numerically simulating thermal convection in a 3-D spherical shell. This is the first study to apply RBFs to a full 3-D physical model in spherical geometry. In addition to being spectrally accurate, RBFs are not defined in terms of any surface-based coordinate system such as spherical coordinates. As a result, when used in the lateral directions, as in this study, they completely circumvent the pole issue with the further advantage that nodes can be "scattered" over the surface of a sphere. In the radial direction, Chebyshev polynomials are used, which are also spectrally accurate and provide the necessary clustering near the boundaries to resolve boundary layers. Applications of this new hybrid methodology are given to the problem of convection in the Earth\\'s mantle, which is modeled by a Boussinesq fluid at infinite Prandtl number. To see whether this numerical technique warrants further investigation, the study limits itself to an isoviscous mantle. Benchmark comparisons are presented with other currently used mantle convection codes for Rayleigh number (Ra) 7 × 10³ and 10⁵. Results from a Ra = 10⁶ simulation are also given. The algorithmic simplicity of the code (mostly due to RBFs) allows it to be written in less than 400 lines of MATLAB and run on a single workstation. We find that our method is very competitive with those currently used in the literature. Copyright 2010 by the American Geophysical Union.

Fitted Fourier-pseudospectral methods for solving a delayed reaction-diffusion partial differential equation in biology

Science.gov (United States)

Adam, A. M. A.; Bashier, E. B. M.; Hashim, M. H. A.; Patidar, K. C.

2017-07-01

In this work, we design and analyze a fitted numerical method to solve a reaction-diffusion model with time delay, namely, a delayed version of a population model which is an extension of the logistic growth (LG) equation for a food-limited population proposed by Smith [F.E. Smith, Population dynamics in Daphnia magna and a new model for population growth, Ecology 44 (1963) 651-663]. Seeing that the analytical solution (in closed form) is hard to obtain, we seek for a robust numerical method. The method consists of a Fourier-pseudospectral semi-discretization in space and a fitted operator implicit-explicit scheme in temporal direction. The proposed method is analyzed for convergence and we found that it is unconditionally stable. Illustrative numerical results will be presented at the conference.

Shifted Legendre method with residual error estimation for delay linear Fredholm integro-differential equations

Directory of Open Access Journals (Sweden)

Şuayip Yüzbaşı

2017-03-01

Full Text Available In this paper, we suggest a matrix method for obtaining the approximate solutions of the delay linear Fredholm integro-differential equations with constant coefficients using the shifted Legendre polynomials. The problem is considered with mixed conditions. Using the required matrix operations, the delay linear Fredholm integro-differential equation is transformed into a matrix equation. Additionally, error analysis for the method is presented using the residual function. Illustrative examples are given to demonstrate the efficiency of the method. The results obtained in this study are compared with the known results.

A summation formula over the zeros of a combination of the associated Legendre functions with a physical application

International Nuclear Information System (INIS)

Saharian, A A

2009-01-01

By using the generalized Abel-Plana formula, we derive a summation formula for the series over the zeros of a combination of the associated Legendre functions with respect to the degree. The summation formula for the series over the zeros of the combination of the Bessel functions, previously discussed in the literature, is obtained as a limiting case. As an application we evaluate the Wightman function for a scalar field with a general curvature coupling parameter in the region between concentric spherical shells on a background of constant negative curvature space. For the Dirichlet boundary conditions the corresponding mode-sum contains the series over the zeros of the combination of the associated Legendre functions. The application of the summation formula allows us to present the Wightman function in the form of the sum of two integrals. The first one corresponds to the Wightman function for the geometry of a single spherical shell and the second one is induced by the presence of the second shell. The boundary-induced part in the vacuum expectation value of the field squared is investigated. For points away from the boundaries the corresponding renormalization procedure is reduced to that for the boundary-free part.

Two Efficient Generalized Laguerre Spectral Algorithms for Fractional Initial Value Problems

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D. Baleanu

2013-01-01

Full Text Available We present a direct solution technique for approximating linear multiterm fractional differential equations (FDEs on semi-infinite interval, using generalized Laguerre polynomials. We derive the operational matrix of Caputo fractional derivative of the generalized Laguerre polynomials which is applied together with generalized Laguerre tau approximation for implementing a spectral solution of linear multiterm FDEs on semi-infinite interval subject to initial conditions. The generalized Laguerre pseudo-spectral approximation based on the generalized Laguerre operational matrix is investigated to reduce the nonlinear multiterm FDEs and its initial conditions to nonlinear algebraic system, thus greatly simplifying the problem. Through several numerical examples, we confirm the accuracy and performance of the proposed spectral algorithms. Indeed, the methods yield accurate results, and the exact solutions are achieved for some tested problems.

Numerical study of nonlinear singular fractional differential equations arising in biology by operational matrix of shifted Legendre polynomials

Directory of Open Access Journals (Sweden)

D. Jabari Sabeg

2016-10-01

Full Text Available In this paper, we present a new computational method for solving nonlinear singular boundary value problems of fractional order arising in biology. To this end, we apply the operational matrices of derivatives of shifted Legendre polynomials to reduce such problems to a system of nonlinear algebraic equations. To demonstrate the validity and applicability of the presented method, we present some numerical examples.

Method of moments solution of volume integral equations using higher-order hierarchical Legendre basis functions

DEFF Research Database (Denmark)

Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter

2004-01-01

An efficient higher-order method of moments (MoM) solution of volume integral equations is presented. The higher-order MoM solution is based on higher-order hierarchical Legendre basis functions and higher-order geometry modeling. An unstructured mesh composed of 8-node trilinear and/or curved 27...... of magnitude in comparison to existing higher-order hierarchical basis functions. Consequently, an iterative solver can be applied even for high expansion orders. Numerical results demonstrate excellent agreement with the analytical Mie series solution for a dielectric sphere as well as with results obtained...

Spherical space Bessel-Legendre-Fourier mode solver for Maxwell's wave equations

Science.gov (United States)

Alzahrani, Mohammed A.; Gauthier, Robert C.

2015-02-01

For spherically symmetric dielectric structures, a basis set composed of Bessel, Legendre and Fourier functions, BLF, are used to cast Maxwell's wave equations into an eigenvalue problem from which the localized modes can be determined. The steps leading to the eigenmatrix are reviewed and techniques used to reduce the order of matrix and tune the computations for particular mode types are detailed. The BLF basis functions are used to expand the electric and magnetic fields as well as the inverse relative dielectric profile. Similar to the common plane wave expansion technique, the BLF matrix returns the eigen-frequencies and eigenvectors, but in BLF only steady states, non-propagated, are obtained. The technique is first applied to a air filled spherical structure with perfectly conducting outer surface and then to a spherical microsphere located in air. Results are compared published values were possible.

Scaling of a Fast Fourier Transform and a pseudo-spectral fluid solver up to 196608 cores

KAUST Repository

Chatterjee, Anando G.

2017-11-04

In this paper we present scaling results of a FFT library, FFTK, and a pseudospectral code, Tarang, on grid resolutions up to 81923 grid using 65536 cores of Blue Gene/P and 196608 cores of Cray XC40 supercomputers. We observe that communication dominates computation, more so on the Cray XC40. The computation time scales as Tcomp∼p−1, and the communication time as Tcomm∼n−γ2 with γ2 ranging from 0.7 to 0.9 for Blue Gene/P, and from 0.43 to 0.73 for Cray XC40. FFTK, and the fluid and convection solvers of Tarang exhibit weak as well as strong scaling nearly up to 196608 cores of Cray XC40. We perform a comparative study of the performance on the Blue Gene/P and Cray XC40 clusters.

Scaling of a Fast Fourier Transform and a pseudo-spectral fluid solver up to 196608 cores

KAUST Repository

Chatterjee, Anando G.; Verma, Mahendra K.; Kumar, Abhishek; Samtaney, Ravi; Hadri, Bilel; Khurram, Rooh Ul Amin

2017-01-01

In this paper we present scaling results of a FFT library, FFTK, and a pseudospectral code, Tarang, on grid resolutions up to 81923 grid using 65536 cores of Blue Gene/P and 196608 cores of Cray XC40 supercomputers. We observe that communication dominates computation, more so on the Cray XC40. The computation time scales as Tcomp∼p−1, and the communication time as Tcomm∼n−γ2 with γ2 ranging from 0.7 to 0.9 for Blue Gene/P, and from 0.43 to 0.73 for Cray XC40. FFTK, and the fluid and convection solvers of Tarang exhibit weak as well as strong scaling nearly up to 196608 cores of Cray XC40. We perform a comparative study of the performance on the Blue Gene/P and Cray XC40 clusters.

Reconstruction of convex bodies from moments

DEFF Research Database (Denmark)

Hörrmann, Julia; Kousholt, Astrid

We investigate how much information about a convex body can be retrieved from a finite number of its geometric moments. We give a sufficient condition for a convex body to be uniquely determined by a finite number of its geometric moments, and we show that among all convex bodies, those which......- rithm that approximates a convex body using a finite number of its Legendre moments. The consistency of the algorithm is established using the stabil- ity result for Legendre moments. When only noisy measurements of Legendre moments are available, the consistency of the algorithm is established under...

[Application of an Adaptive Inertia Weight Particle Swarm Algorithm in the Magnetic Resonance Bias Field Correction].

Science.gov (United States)

Wang, Chang; Qin, Xin; Liu, Yan; Zhang, Wenchao

2016-06-01

An adaptive inertia weight particle swarm algorithm is proposed in this study to solve the local optimal problem with the method of traditional particle swarm optimization in the process of estimating magnetic resonance(MR)image bias field.An indicator measuring the degree of premature convergence was designed for the defect of traditional particle swarm optimization algorithm.The inertia weight was adjusted adaptively based on this indicator to ensure particle swarm to be optimized globally and to avoid it from falling into local optimum.The Legendre polynomial was used to fit bias field,the polynomial parameters were optimized globally,and finally the bias field was estimated and corrected.Compared to those with the improved entropy minimum algorithm,the entropy of corrected image was smaller and the estimated bias field was more accurate in this study.Then the corrected image was segmented and the segmentation accuracy obtained in this research was 10% higher than that with improved entropy minimum algorithm.This algorithm can be applied to the correction of MR image bias field.

openPSTD: The open source pseudospectral time-domain method for acoustic propagation

Science.gov (United States)

Hornikx, Maarten; Krijnen, Thomas; van Harten, Louis

2016-06-01

An open source implementation of the Fourier pseudospectral time-domain (PSTD) method for computing the propagation of sound is presented, which is geared towards applications in the built environment. Being a wave-based method, PSTD captures phenomena like diffraction, but maintains efficiency in processing time and memory usage as it allows to spatially sample close to the Nyquist criterion, thus keeping both the required spatial and temporal resolution coarse. In the implementation it has been opted to model the physical geometry as a composition of rectangular two-dimensional subdomains, hence initially restricting the implementation to orthogonal and two-dimensional situations. The strategy of using subdomains divides the problem domain into local subsets, which enables the simulation software to be built according to Object-Oriented Programming best practices and allows room for further computational parallelization. The software is built using the open source components, Blender, Numpy and Python, and has been published under an open source license itself as well. For accelerating the software, an option has been included to accelerate the calculations by a partial implementation of the code on the Graphical Processing Unit (GPU), which increases the throughput by up to fifteen times. The details of the implementation are reported, as well as the accuracy of the code.

Monte Carlo Calculation of Sensitivities to Secondaries' Angular Distributions

International Nuclear Information System (INIS)

Perel, R.L.

2003-01-01

An algorithm for Monte Carlo calculation of sensitivities of responses to secondaries' angular distributions (SAD) is developed, based on the differential operator approach. The algorithm was formulated for the sensitivity to Legendre coefficients of the SAD and is valid even in cases where the actual representation of SAD is not in the form of a Legendre series. The algorithm was implemented, for point- or ring-detectors, in a local version of the code MCNP. Numerical tests were performed to validate the algorithm and its implementation. In addition, an algorithm specific for the Kalbach-Mann representation of SAD is presented

Algorithms for Computing the Magnetic Field, Vector Potential, and Field Derivatives for Circular Current Loops in Cylindrical Coordinates

Energy Technology Data Exchange (ETDEWEB)

Walstrom, Peter Lowell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-08-24

A numerical algorithm for computing the field components B_r and B_z and their r and z derivatives with open boundaries in cylindrical coordinates for circular current loops is described. An algorithm for computing the vector potential is also described. For the convenience of the reader, derivations of the final expressions from their defining integrals are given in detail, since their derivations (especially for the field derivatives) are not all easily found in textbooks. Numerical calculations are based on evaluation of complete elliptic integrals using the Bulirsch algorithm cel. Since cel can evaluate complete elliptic integrals of a fairly general type, in some cases the elliptic integrals can be evaluated without first reducing them to forms containing standard Legendre forms. The algorithms avoid the numerical difficulties that many of the textbook solutions have for points near the axis because of explicit factors of 1=r or 1=r² in the some of the expressions.

Evaluation of integrals involving powers of (1-x2) and two associated Legendre functions or Gegenbauer polynomials

International Nuclear Information System (INIS)

Rashid, M.A.

1984-08-01

Integrals involving powers of (1-x 2 ) and two associated Legendre functions or two Gegenbauer polynomials are evaluated as finite sums which can be expressed in terms of terminating hypergeometric function 4 F 3 . The integrals which are evaluated are ∫sub(-1)sup(1)[Psub(l)sup(m)(x)Psub(k)sup(n)(x)]/[(1-x 2 )sup(p+1)]dx and ∫sub(-1)sup(1)Csub(l)sup(α)(x)Csub(k)sup(β)(x)[(1-x 2 )sup[(α+β-3)/2-p

Numerical Solution of the Fractional Partial Differential Equations by the Two-Dimensional Fractional-Order Legendre Functions

Directory of Open Access Journals (Sweden)

Fukang Yin

2013-01-01

Full Text Available A numerical method is presented to obtain the approximate solutions of the fractional partial differential equations (FPDEs. The basic idea of this method is to achieve the approximate solutions in a generalized expansion form of two-dimensional fractional-order Legendre functions (2D-FLFs. The operational matrices of integration and derivative for 2D-FLFs are first derived. Then, by these matrices, a system of algebraic equations is obtained from FPDEs. Hence, by solving this system, the unknown 2D-FLFs coefficients can be computed. Three examples are discussed to demonstrate the validity and applicability of the proposed method.

Homotopy Algorithm for Optimal Control Problems with a Second-order State Constraint

International Nuclear Information System (INIS)

Hermant, Audrey

2010-01-01

This paper deals with optimal control problems with a regular second-order state constraint and a scalar control, satisfying the strengthened Legendre-Clebsch condition. We study the stability of structure of stationary points. It is shown that under a uniform strict complementarity assumption, boundary arcs are stable under sufficiently smooth perturbations of the data. On the contrary, nonreducible touch points are not stable under perturbations. We show that under some reasonable conditions, either a boundary arc or a second touch point may appear. Those results allow us to design an homotopy algorithm which automatically detects the structure of the trajectory and initializes the shooting parameters associated with boundary arcs and touch points.

A pseudospectral matrix method for time-dependent tensor fields on a spherical shell

International Nuclear Information System (INIS)

Brügmann, Bernd

2013-01-01

We construct a pseudospectral method for the solution of time-dependent, non-linear partial differential equations on a three-dimensional spherical shell. The problem we address is the treatment of tensor fields on the sphere. As a test case we consider the evolution of a single black hole in numerical general relativity. A natural strategy would be the expansion in tensor spherical harmonics in spherical coordinates. Instead, we consider the simpler and potentially more efficient possibility of a double Fourier expansion on the sphere for tensors in Cartesian coordinates. As usual for the double Fourier method, we employ a filter to address time-step limitations and certain stability issues. We find that a tensor filter based on spin-weighted spherical harmonics is successful, while two simplified, non-spin-weighted filters do not lead to stable evolutions. The derivatives and the filter are implemented by matrix multiplication for efficiency. A key technical point is the construction of a matrix multiplication method for the spin-weighted spherical harmonic filter. As example for the efficient parallelization of the double Fourier, spin-weighted filter method we discuss an implementation on a GPU, which achieves a speed-up of up to a factor of 20 compared to a single core CPU implementation

Legendre transform structure and extremal properties of the relative Fisher information

Energy Technology Data Exchange (ETDEWEB)

Venkatesan, R.C., E-mail: ravi@systemsresearchcorp.com [Systems Research Corporation, Aundh, Pune 411007 (India); Plastino, A., E-mail: plastino@fisica.unlp.edu.ar [IFLP, National University La Plata and National Research Council (CONICET) C.C., 727 1900 La Plata (Argentina)

2014-04-01

Variational extremization of the relative Fisher information (RFI, hereafter) is performed. Reciprocity relations, akin to those of thermodynamics are derived, employing the extremal results of the RFI expressed in terms of probability amplitudes. A time independent Schrödinger-like equation (Schrödinger-like link) for the RFI is derived. The concomitant Legendre transform structure (LTS, hereafter) is developed by utilizing a generalized RFI-Euler theorem, which shows that the entire mathematical structure of thermodynamics translates into the RFI framework, both for equilibrium and non-equilibrium cases. The qualitatively distinct nature of the present results vis-á-vis those of prior studies utilizing the Shannon entropy and/or the Fisher information measure (FIM, hereafter) is discussed. A principled relationship between the RFI and the FIM frameworks is derived. The utility of this relationship is demonstrated by an example wherein the energy eigenvalues of the Schrödinger-like link for the RFI are inferred solely using the quantum mechanical virial theorem and the LTS of the RFI.

Hybrid Fourier pseudospectral/discontinuous Galerkin time-domain method for wave propagation

Science.gov (United States)

Pagán Muñoz, Raúl; Hornikx, Maarten

2017-11-01

The Fourier Pseudospectral time-domain (Fourier PSTD) method was shown to be an efficient way of modelling acoustic propagation problems as described by the linearized Euler equations (LEE), but is limited to real-valued frequency independent boundary conditions and predominantly staircase-like boundary shapes. This paper presents a hybrid approach to solve the LEE, coupling Fourier PSTD with a nodal Discontinuous Galerkin (DG) method. DG exhibits almost no restrictions with respect to geometrical complexity or boundary conditions. The aim of this novel method is to allow the computation of complex geometries and to be a step towards the implementation of frequency dependent boundary conditions by using the benefits of DG at the boundaries, while keeping the efficient Fourier PSTD in the bulk of the domain. The hybridization approach is based on conformal meshes to avoid spatial interpolation of the DG solutions when transferring values from DG to Fourier PSTD, while the data transfer from Fourier PSTD to DG is done utilizing spectral interpolation of the Fourier PSTD solutions. The accuracy of the hybrid approach is presented for one- and two-dimensional acoustic problems and the main sources of error are investigated. It is concluded that the hybrid methodology does not introduce significant errors compared to the Fourier PSTD stand-alone solver. An example of a cylinder scattering problem is presented and accurate results have been obtained when using the proposed approach. Finally, no instabilities were found during long-time calculation using the current hybrid methodology on a two-dimensional domain.

Study of the influence of semiconductor material parameters on acoustic wave propagation modes in GaSb/AlSb bi-layered structures by Legendre polynomial method

Energy Technology Data Exchange (ETDEWEB)

Othmani, Cherif, E-mail: othmanicheriffss@gmail.com; Takali, Farid; Njeh, Anouar; Ben Ghozlen, Mohamed Hédi

2016-09-01

The propagation of Rayleigh–Lamb waves in bi-layered structures is studied. For this purpose, an extension of the Legendre polynomial (LP) method is proposed to formulate the acoustic wave equation in the bi-layered structures induced by thin film Gallium Antimonide (GaSb) and with Aluminum Antimonide (AlSb) substrate in moderate thickness. Acoustic modes propagating along a bi-layer plate are shown to be quite different than classical Lamb modes, contrary to most of the multilayered structures. The validation of the LP method is illustrated by a comparison between the associated numerical results and those obtained using the ordinary differential equation (ODE) method. The convergency of the LP method is discussed through a numerical example. Moreover, the influences of thin film GaSb parameters on the characteristics Rayleigh–Lamb waves propagation has been studied in detail. Finally, the advantages of the Legendre polynomial (LP) method to analyze the multilayered structures are described. All the developments performed in this work were implemented in Matlab software.

Study of the influence of semiconductor material parameters on acoustic wave propagation modes in GaSb/AlSb bi-layered structures by Legendre polynomial method

International Nuclear Information System (INIS)

Othmani, Cherif; Takali, Farid; Njeh, Anouar; Ben Ghozlen, Mohamed Hédi

2016-01-01

The propagation of Rayleigh–Lamb waves in bi-layered structures is studied. For this purpose, an extension of the Legendre polynomial (LP) method is proposed to formulate the acoustic wave equation in the bi-layered structures induced by thin film Gallium Antimonide (GaSb) and with Aluminum Antimonide (AlSb) substrate in moderate thickness. Acoustic modes propagating along a bi-layer plate are shown to be quite different than classical Lamb modes, contrary to most of the multilayered structures. The validation of the LP method is illustrated by a comparison between the associated numerical results and those obtained using the ordinary differential equation (ODE) method. The convergency of the LP method is discussed through a numerical example. Moreover, the influences of thin film GaSb parameters on the characteristics Rayleigh–Lamb waves propagation has been studied in detail. Finally, the advantages of the Legendre polynomial (LP) method to analyze the multilayered structures are described. All the developments performed in this work were implemented in Matlab software.

American Conference on Theoretical Chemistry Held in Gull Lake, Minnesota on July 25-31, 1987.

Science.gov (United States)

1988-01-01

Texas 78712 ABSTRACT A new algorithm for self-consistent electronic structure calculations has been developed. The algorithm is a synthesis of...calculations has been developed. The algorithm is a synthesis of conventional electronic structure techniques with the pseudospectral method, a numerical...formanilide and trimethylamine represent possible associative sites of the local P anesthetics procaine and lidocaine . Dimethylphosphate monoanion, o

Ring-Shaped Potential and a Class of Relevant Integrals Involved Universal Associated Legendre Polynomials with Complicated Arguments

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Wei Li

2017-01-01

Full Text Available We find that the solution of the polar angular differential equation can be written as the universal associated Legendre polynomials. Its generating function is applied to obtain an analytical result for a class of interesting integrals involving complicated argument, that is, ∫-11Pl′m′xt-1/1+t2-2xtPk′m′(x/(1+t2-2tx(l′+1/2dx, where t∈(0,1. The present method can in principle be generalizable to the integrals involving other special functions. As an illustration we also study a typical Bessel integral with a complicated argument ∫0∞Jn(αx2+z2/(x2+z2nx2m+1dx.

Mapped Chebyshev Pseudo-Spectral Method for Dynamic Aero-Elastic Problem of Limit Cycle Oscillation

Science.gov (United States)

Im, Dong Kyun; Kim, Hyun Soon; Choi, Seongim

2018-05-01

A mapped Chebyshev pseudo-spectral method is developed as one of the Fourier-spectral approaches and solves nonlinear PDE systems for unsteady flows and dynamic aero-elastic problem in a given time interval, where the flows or elastic motions can be periodic, nonperiodic, or periodic with an unknown frequency. The method uses the Chebyshev polynomials of the first kind for the basis function and redistributes the standard Chebyshev-Gauss-Lobatto collocation points more evenly by a conformal mapping function for improved numerical stability. Contributions of the method are several. It can be an order of magnitude more efficient than the conventional finite difference-based, time-accurate computation, depending on the complexity of solutions and the number of collocation points. The method reformulates the dynamic aero-elastic problem in spectral form for coupled analysis of aerodynamics and structures, which can be effective for design optimization of unsteady and dynamic problems. A limit cycle oscillation (LCO) is chosen for the validation and a new method to determine the LCO frequency is introduced based on the minimization of a second derivative of the aero-elastic formulation. Two examples of the limit cycle oscillation are tested: nonlinear, one degree-of-freedom mass-spring-damper system and two degrees-of-freedom oscillating airfoil under pitch and plunge motions. Results show good agreements with those of the conventional time-accurate simulations and wind tunnel experiments.

Dynamics of one-dimensional self-gravitating systems using Hermite-Legendre polynomials

Science.gov (United States)

Barnes, Eric I.; Ragan, Robert J.

2014-01-01

The current paradigm for understanding galaxy formation in the Universe depends on the existence of self-gravitating collisionless dark matter. Modelling such dark matter systems has been a major focus of astrophysicists, with much of that effort directed at computational techniques. Not surprisingly, a comprehensive understanding of the evolution of these self-gravitating systems still eludes us, since it involves the collective non-linear dynamics of many particle systems interacting via long-range forces described by the Vlasov equation. As a step towards developing a clearer picture of collisionless self-gravitating relaxation, we analyse the linearized dynamics of isolated one-dimensional systems near thermal equilibrium by expanding their phase-space distribution functions f(x, v) in terms of Hermite functions in the velocity variable, and Legendre functions involving the position variable. This approach produces a picture of phase-space evolution in terms of expansion coefficients, rather than spatial and velocity variables. We obtain equations of motion for the expansion coefficients for both test-particle distributions and self-gravitating linear perturbations of thermal equilibrium. N-body simulations of perturbed equilibria are performed and found to be in excellent agreement with the expansion coefficient approach over a time duration that depends on the size of the expansion series used.

Recent advances in the modeling of plasmas with the Particle-In-Cell methods

Science.gov (United States)

Vay, Jean-Luc; Lehe, Remi; Vincenti, Henri; Godfrey, Brendan; Lee, Patrick; Haber, Irv

2015-11-01

The Particle-In-Cell (PIC) approach is the method of choice for self-consistent simulations of plasmas from first principles. The fundamentals of the PIC method were established decades ago but improvements or variations are continuously being proposed. We report on several recent advances in PIC related algorithms, including: (a) detailed analysis of the numerical Cherenkov instability and its remediation, (b) analytic pseudo-spectral electromagnetic solvers in Cartesian and cylindrical (with azimuthal modes decomposition) geometries, (c) arbitrary-order finite-difference and generalized pseudo-spectral Maxwell solvers, (d) novel analysis of Maxwell's solvers' stencil variation and truncation, in application to domain decomposition strategies and implementation of Perfectly Matched Layers in high-order and pseudo-spectral solvers. Work supported by US-DOE Contracts DE-AC02-05CH11231 and the US-DOE SciDAC program ComPASS. Used resources of NERSC, supported by US-DOE Contract DE-AC02-05CH11231.

Numerical Solution of a Fractional Order Model of HIV Infection of CD4+T Cells Using Müntz-Legendre Polynomials

Directory of Open Access Journals (Sweden)

Mojtaba Rasouli Gandomani

2016-06-01

Full Text Available In this paper, the model of HIV infection of CD4+ T cells is considered as a system of fractional differential equations. Then, a numerical method by using collocation method based on the Müntz-Legendre polynomials to approximate solution of the model is presented. The application of the proposed numerical method causes fractional differential equations system to convert into the algebraic equations system. The new system can be solved by one of the existing methods. Finally, we compare the result of this numerical method with the result of the methods have already been presented in the literature.

Displaced Electric Sail Orbits Design and Transition Trajectory Optimization

Directory of Open Access Journals (Sweden)

Naiming Qi

2014-01-01

Full Text Available Displaced orbits for spacecraft propelled by electric sails are investigated as an alternative to the use of solar sails. The orbital dynamics of electric sails based spacecraft are studied within a spherical coordinate system, which permits finding the solutions of displaced electric sail orbits and optimize transfer trajectory. Transfer trajectories from Earth's orbit to displaced orbit are also studied in an optimal framework, by using genetic algorithm and Gauss pseudospectral method. The initial guesses for the state and control histories used in the Gauss pseudospectral method are interpolated from the best solution of a genetic algorithm. Numerical simulations show that the electric sail is able to perform the transfer from Earth’s orbit to displaced orbit in acceptable time, and the hybrid optimization method has the capability to search the feasible and optimal solution without any initial value guess.

THE PSTD ALGORITHM: A TIME-DOMAIN METHOD REQUIRING ONLY TWO CELLS PER WAVELENGTH. (R825225)

Science.gov (United States)

A pseudospectral time-domain (PSTD) method is developed for solutions of Maxwell's equations. It uses the fast Fourier transform (FFT), instead of finite differences on conventional finite-difference-time-domain (FDTD) methods, to represent spatial derivatives. Because the Fourie...

A Novel Medical Image Watermarking in Three-dimensional Fourier Compressed Domain

Directory of Open Access Journals (Sweden)

Baoru Han

2015-09-01

Full Text Available Digital watermarking is a research hotspot in the field of image security, which is protected digital image copyright. In order to ensure medical image information security, a novel medical image digital watermarking algorithm in three-dimensional Fourier compressed domain is proposed. The novel medical image digital watermarking algorithm takes advantage of three-dimensional Fourier compressed domain characteristics, Legendre chaotic neural network encryption features and robust characteristics of differences hashing, which is a robust zero-watermarking algorithm. On one hand, the original watermarking image is encrypted in order to enhance security. It makes use of Legendre chaotic neural network implementation. On the other hand, the construction of zero-watermarking adopts differences hashing in three-dimensional Fourier compressed domain. The novel watermarking algorithm does not need to select a region of interest, can solve the problem of medical image content affected. The specific implementation of the algorithm and the experimental results are given in the paper. The simulation results testify that the novel algorithm possesses a desirable robustness to common attack and geometric attack.

A New Finite Difference Q-compensated RTM Algorithm in Tilted Transverse Isotropic (TTI) Media

Science.gov (United States)

Zhou, T.; Hu, W.; Ning, J.

2017-12-01

Attenuating anisotropic geological body is difficult to image with conventional migration methods. In such kind of scenarios, recorded seismic data suffer greatly from both amplitude decay and phase distortion, resulting in degraded resolution, poor illumination and incorrect migration depth in imaging results. To efficiently obtain high quality images, we propose a novel TTI QRTM algorithm based on Generalized Standard Linear Solid model combined with a unique multi-stage optimization technique to simultaneously correct the decayed amplitude and the distorted phase velocity. Numerical tests (shown in the figure) demonstrate that our TTI QRTM algorithm effectively corrects migration depth, significantly improves illumination, and enhances resolution within and below the low Q regions. The result of our new method is very close to the reference RTM image, while QRTM without TTI cannot get a correct image. Compared to the conventional QRTM method based on a pseudo-spectral operator for fractional Laplacian evaluation, our method is more computationally efficient for large scale applications and more suitable for GPU acceleration. With the current multi-stage dispersion optimization scheme, this TTI QRTM method best performs in the frequency range 10-70 Hz, and could be used in a wider frequency range. Furthermore, as this method can also handle frequency dependent Q, it has potential to be applied in imaging deep structures where low Q exists, such as subduction zones, volcanic zones or fault zones with passive source observations.

Scalable explicit implementation of anisotropic diffusion with Runge-Kutta-Legendre super-time stepping

Science.gov (United States)

Vaidya, Bhargav; Prasad, Deovrat; Mignone, Andrea; Sharma, Prateek; Rickler, Luca

2017-12-01

An important ingredient in numerical modelling of high temperature magnetized astrophysical plasmas is the anisotropic transport of heat along magnetic field lines from higher to lower temperatures. Magnetohydrodynamics typically involves solving the hyperbolic set of conservation equations along with the induction equation. Incorporating anisotropic thermal conduction requires to also treat parabolic terms arising from the diffusion operator. An explicit treatment of parabolic terms will considerably reduce the simulation time step due to its dependence on the square of the grid resolution (Δx) for stability. Although an implicit scheme relaxes the constraint on stability, it is difficult to distribute efficiently on a parallel architecture. Treating parabolic terms with accelerated super-time-stepping (STS) methods has been discussed in literature, but these methods suffer from poor accuracy (first order in time) and also have difficult-to-choose tuneable stability parameters. In this work, we highlight a second-order (in time) Runge-Kutta-Legendre (RKL) scheme (first described by Meyer, Balsara & Aslam 2012) that is robust, fast and accurate in treating parabolic terms alongside the hyperbolic conversation laws. We demonstrate its superiority over the first-order STS schemes with standard tests and astrophysical applications. We also show that explicit conduction is particularly robust in handling saturated thermal conduction. Parallel scaling of explicit conduction using RKL scheme is demonstrated up to more than 104 processors.

Normalization and Implementation of Three Gravitational Acceleration Models

Science.gov (United States)

Eckman, Randy A.; Brown, Aaron J.; Adamo, Daniel R.; Gottlieb, Robert G.

2016-01-01

Unlike the uniform density spherical shell approximations of Newton, the consequence of spaceflight in the real universe is that gravitational fields are sensitive to the asphericity of their generating central bodies. The gravitational potential of an aspherical central body is typically resolved using spherical harmonic approximations. However, attempting to directly calculate the spherical harmonic approximations results in at least two singularities that must be removed to generalize the method and solve for any possible orbit, including polar orbits. Samuel Pines, Bill Lear, and Robert Gottlieb developed three unique algorithms to eliminate these singularities. This paper documents the methodical normalization of two of the three known formulations for singularity-free gravitational acceleration (namely, the Lear and Gottlieb algorithms) and formulates a general method for defining normalization parameters used to generate normalized Legendre polynomials and Associated Legendre Functions (ALFs) for any algorithm. A treatment of the conventional formulation of the gravitational potential and acceleration is also provided, in addition to a brief overview of the philosophical differences between the three known singularity-free algorithms.

Investigation of multi-dimensional computational models for calculating pollutant transport

International Nuclear Information System (INIS)

Pepper, D.W.; Cooper, R.E.; Baker, A.J.

1980-01-01

A performance study of five numerical solution algorithms for multi-dimensional advection-diffusion prediction on mesoscale grids was made. Test problems include transport of point and distributed sources, and a simulation of a continuous source. In all cases, analytical solutions are available to assess relative accuracy. The particle-in-cell and second-moment algorithms, both of which employ sub-grid resolution coupled with Lagrangian advection, exhibit superior accuracy in modeling a point source release. For modeling of a distributed source, algorithms based upon the pseudospectral and finite element interpolation concepts, exhibit improved accuracy on practical discretizations

Positive Scattering Cross Sections using Constrained Least Squares

International Nuclear Information System (INIS)

Dahl, J.A.; Ganapol, B.D.; Morel, J.E.

1999-01-01

A method which creates a positive Legendre expansion from truncated Legendre cross section libraries is presented. The cross section moments of order two and greater are modified by a constrained least squares algorithm, subject to the constraints that the zeroth and first moments remain constant, and that the standard discrete ordinate scattering matrix is positive. A method using the maximum entropy representation of the cross section which reduces the error of these modified moments is also presented. These methods are implemented in PARTISN, and numerical results from a transport calculation using highly anisotropic scattering cross sections with the exponential discontinuous spatial scheme is presented

Efficient, approximate and parallel Hartree-Fock and hybrid DFT calculations. A 'chain-of-spheres' algorithm for the Hartree-Fock exchange

International Nuclear Information System (INIS)

Neese, Frank; Wennmohs, Frank; Hansen, Andreas; Becker, Ute

2009-01-01

In this paper, the possibility is explored to speed up Hartree-Fock and hybrid density functional calculations by forming the Coulomb and exchange parts of the Fock matrix by different approximations. For the Coulomb part the previously introduced Split-RI-J variant (F. Neese, J. Comput. Chem. 24 (2003) 1740) of the well-known 'density fitting' approximation is used. The exchange part is formed by semi-numerical integration techniques that are closely related to Friesner's pioneering pseudo-spectral approach. Our potentially linear scaling realization of this algorithm is called the 'chain-of-spheres exchange' (COSX). A combination of semi-numerical integration and density fitting is also proposed. Both Split-RI-J and COSX scale very well with the highest angular momentum in the basis sets. It is shown that for extended basis sets speed-ups of up to two orders of magnitude compared to traditional implementations can be obtained in this way. Total energies are reproduced with an average error of <0.3 kcal/mol as determined from extended test calculations with various basis sets on a set of 26 molecules with 20-200 atoms and up to 2000 basis functions. Reaction energies agree to within 0.2 kcal/mol (Hartree-Fock) or 0.05 kcal/mol (hybrid DFT) with the canonical values. The COSX algorithm parallelizes with a speedup of 8.6 observed for 10 processes. Minimum energy geometries differ by less than 0.3 pm in the bond distances and 0.5 deg. in the bond angels from their canonical values. These developments enable highly efficient and accurate self-consistent field calculations including nonlocal Hartree-Fock exchange for large molecules. In combination with the RI-MP2 method and large basis sets, second-order many body perturbation energies can be obtained for medium sized molecules with unprecedented efficiency. The algorithms are implemented into the ORCA electronic structure system

Preliminary analysis of four numerical models for calculating the mesoscale transport of Kr-85

Energy Technology Data Exchange (ETDEWEB)

Pepper, D W; Cooper, R E [Du Pont de Nemours (E.I.) and Co., Aiken, SC (USA). Savannah River Lab.

1983-01-01

A performance study of four numerical algorithms for multi-dimensional advection-diffusion prediction on mesoscale grids has been made. Dispersion from point and distributed sources and a simulation of a continuous source are compared with analytical solutions to assess relative accuracy. Model predictions are then compared with actual measurements of Kr-85 emitted from the Savannah River Plant (SRP). The particle-in-cell and method of moments algorithms exhibit superior accuracy in modeling single source releases. For modeling distributed sources, algorithms based on the pseudospectral and finite element interpolation concepts exhibit comparable accuracy. The method of moments is felt to be the best overall performer, although all the models appear to be relatively close in accuracy.

Adaptive mesh refinement with spectral accuracy for magnetohydrodynamics in two space dimensions

International Nuclear Information System (INIS)

Rosenberg, D; Pouquet, A; Mininni, P D

2007-01-01

We examine the effect of accuracy of high-order spectral element methods, with or without adaptive mesh refinement (AMR), in the context of a classical configuration of magnetic reconnection in two space dimensions, the so-called Orszag-Tang (OT) vortex made up of a magnetic X-point centred on a stagnation point of the velocity. A recently developed spectral-element adaptive refinement incompressible magnetohydrodynamic (MHD) code is applied to simulate this problem. The MHD solver is explicit, and uses the Elsaesser formulation on high-order elements. It automatically takes advantage of the adaptive grid mechanics that have been described elsewhere in the fluid context (Rosenberg et al 2006 J. Comput. Phys. 215 59-80); the code allows both statically refined and dynamically refined grids. Tests of the algorithm using analytic solutions are described, and comparisons of the OT solutions with pseudo-spectral computations are performed. We demonstrate for moderate Reynolds numbers that the algorithms using both static and refined grids reproduce the pseudo-spectral solutions quite well. We show that low-order truncation-even with a comparable number of global degrees of freedom-fails to correctly model some strong (sup-norm) quantities in this problem, even though it satisfies adequately the weak (integrated) balance diagnostics

Semi-implicit magnetohydrodynamic calculations

International Nuclear Information System (INIS)

Schnack, D.D.; Barnes, D.C.; Mikic, Z.; Harned, D.S.; Caramana, E.J.

1987-01-01

A semi-implicit algorithm for the solution of the nonlinear, three-dimensional, resistive MHD equations in cylindrical geometry is presented. The specific model assumes uniform density and pressure, although this is not a restriction of the method. The spatial approximation employs finite differences in the radial coordinate, and the pseudo-spectral algorithm in the periodic poloidal and axial coordinates. A leapfrog algorithm is used to advance wave-like terms; advective terms are treated with a simple predictor--corrector method. The semi-implicit term is introduced as a simple modification to the momentum equation. Dissipation is treated implicitly. The resulting algorithm is unconditionally stable with respect to normal modes. A general discussion of the semi-implicit method is given, and specific forms of the semi-implicit operator are compared in physically relevant test cases. Long-time simulations are presented. copyright 1987 Academic Press, Inc

The hybrid model for sampling multiple elastic scattering angular deflections based on Goudsmit-Saunderson theory

Directory of Open Access Journals (Sweden)

Wasaye Muhammad Abdul

2017-01-01

Full Text Available An algorithm for the Monte Carlo simulation of electron multiple elastic scattering based on the framework of SuperMC (Super Monte Carlo simulation program for nuclear and radiation process is presented. This paper describes efficient and accurate methods by which the multiple scattering angular deflections are sampled. The Goudsmit-Saunderson theory of multiple scattering has been used for sampling angular deflections. Differential cross-sections of electrons and positrons by neutral atoms have been calculated by using Dirac partial wave program ELSEPA. The Legendre coefficients are accurately computed by using the Gauss-Legendre integration method. Finally, a novel hybrid method for sampling angular distribution has been developed. The model uses efficient rejection sampling method for low energy electrons (500 mean free paths. For small path lengths, a simple, efficient and accurate analytical distribution function has been proposed. The later uses adjustable parameters determined from the fitting of Goudsmith-Saunderson angular distribution. A discussion of the sampling efficiency and accuracy of this newly developed algorithm is given. The efficiency of rejection sampling algorithm is at least 50 % for electron kinetic energies less than 500 keV and longer path lengths (>500 mean free paths. Monte Carlo Simulation results are then compared with measured angular distributions of Ross et al. The comparison shows that our results are in good agreement with experimental measurements.

Study of stratified dielectric slab medium structures using pseudo-spectral time domain (PSTD) algorithm

DEFF Research Database (Denmark)

Tong, M.S.; Lu, Y.; Chen, Y.

2005-01-01

-layer structures are analyzed. Results show that this method matches satisfactorily the Nyquist sampling theorem in terms of spatial discretization. By comparing the given results, it is found that the PSTD method outperforms the finite-difference time-domain (FDTD) method in general, especially in terms...

Self-adaptive numerical integrator for analytic functions

International Nuclear Information System (INIS)

Garribba, S.; Quartapelle, L.; Reina, G.

1978-01-01

A new adaptive algorithm for the integration of analytical functions is presented. The algorithm processes the integration interval by generating local subintervals whose length is controlled through a feedback loop. The control is obtained by means of a relation derived on an analytical basis and valid for an arbitrary integration rule: two different estimates of an integral are used to compute the interval length necessary to obtain an integral estimate with accuracy within the assigned error bounds. The implied method for local generation of subintervals and an effective assumption of error partition among subintervals give rise to an adaptive algorithm provided with a highly accurate and very efficient integration procedure. The particular algorithm obtained by choosing the 6-point Gauss-Legendre integration rule is considered and extensive comparisons are made with other outstanding integration algorithms

Algebraic dynamics algorithm: Numerical comparison with Runge-Kutta algorithm and symplectic geometric algorithm

Institute of Scientific and Technical Information of China (English)

WANG ShunJin; ZHANG Hua

2007-01-01

Based on the exact analytical solution of ordinary differential equations,a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm.A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models.The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision,and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.

Algebraic dynamics algorithm:Numerical comparison with Runge-Kutta algorithm and symplectic geometric algorithm

Institute of Scientific and Technical Information of China (English)

2007-01-01

Based on the exact analytical solution of ordinary differential equations, a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm. A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models. The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision, and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.

The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

Directory of Open Access Journals (Sweden)

Dazhi Jiang

2015-01-01

Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.

Stochastic Real-Time Optimal Control: A Pseudospectral Approach for Bearing-Only Trajectory Optimization

Science.gov (United States)

2011-09-01

measurements suitable for algorithms such as Ekelund or Spiess ranging [104], followed by one extra turn to eliminate ambiguities. A maneuver that...and Dynamics, 7(3), 1984. [104] Spiess , F. N. “Complete Solution of the Bearings Only Approach Problem”. UC San Diego: Scripps Institution of...spectral methods, 21 Spiess ranging, 4 state augmentation, 81 state transition matrix, 66 stereo ranging, 4 sUAS, 5–8, 14, 38, 39, 69, 77, 82, 86, 117, 167

Algorithms

Indian Academy of Sciences (India)

polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.

STAR Algorithm Integration Team - Facilitating operational algorithm development

Science.gov (United States)

Mikles, V. J.

2015-12-01

The NOAA/NESDIS Center for Satellite Research and Applications (STAR) provides technical support of the Joint Polar Satellite System (JPSS) algorithm development and integration tasks. Utilizing data from the S-NPP satellite, JPSS generates over thirty Environmental Data Records (EDRs) and Intermediate Products (IPs) spanning atmospheric, ocean, cryosphere, and land weather disciplines. The Algorithm Integration Team (AIT) brings technical expertise and support to product algorithms, specifically in testing and validating science algorithms in a pre-operational environment. The AIT verifies that new and updated algorithms function in the development environment, enforces established software development standards, and ensures that delivered packages are functional and complete. AIT facilitates the development of new JPSS-1 algorithms by implementing a review approach based on the Enterprise Product Lifecycle (EPL) process. Building on relationships established during the S-NPP algorithm development process and coordinating directly with science algorithm developers, the AIT has implemented structured reviews with self-contained document suites. The process has supported algorithm improvements for products such as ozone, active fire, vegetation index, and temperature and moisture profiles.

Selfish Gene Algorithm Vs Genetic Algorithm: A Review

Science.gov (United States)

Ariff, Norharyati Md; Khalid, Noor Elaiza Abdul; Hashim, Rathiah; Noor, Noorhayati Mohamed

2016-11-01

Evolutionary algorithm is one of the algorithms inspired by the nature. Within little more than a decade hundreds of papers have reported successful applications of EAs. In this paper, the Selfish Gene Algorithms (SFGA), as one of the latest evolutionary algorithms (EAs) inspired from the Selfish Gene Theory which is an interpretation of Darwinian Theory ideas from the biologist Richards Dawkins on 1989. In this paper, following a brief introduction to the Selfish Gene Algorithm (SFGA), the chronology of its evolution is presented. It is the purpose of this paper is to present an overview of the concepts of Selfish Gene Algorithm (SFGA) as well as its opportunities and challenges. Accordingly, the history, step involves in the algorithm are discussed and its different applications together with an analysis of these applications are evaluated.

Algorithms

Indian Academy of Sciences (India)

to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...

Pramana – Journal of Physics | Indian Academy of Sciences

Indian Academy of Sciences (India)

July 2005, pages 1-164. pp 1-15 Research Articles. The generalized pseudospectral approach to the bound states of the Hulthén and the Yukawa potentials · Amlan K Roy · More Details Abstract Fulltext PDF. The generalized pseudospectral (GPS) method is employed to calculate the bound states of the Hulthén and the ...

Algorithmic mathematics

CERN Document Server

Hougardy, Stefan

2016-01-01

Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.

Essential algorithms a practical approach to computer algorithms

CERN Document Server

Stephens, Rod

2013-01-01

A friendly and accessible introduction to the most useful algorithms Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical classic algorithms, and even how to create new algorithms to meet future needs. The book also includes a collection of questions that can help readers prepare for a programming job interview. Reveals methods for manipulating common data structures s

Algorithmic cryptanalysis

CERN Document Server

Joux, Antoine

2009-01-01

Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic

Denni Algorithm An Enhanced Of SMS (Scan, Move and Sort) Algorithm

Science.gov (United States)

Aprilsyah Lubis, Denni; Salim Sitompul, Opim; Marwan; Tulus; Andri Budiman, M.

2017-12-01

Sorting has been a profound area for the algorithmic researchers, and many resources are invested to suggest a more working sorting algorithm. For this purpose many existing sorting algorithms were observed in terms of the efficiency of the algorithmic complexity. Efficient sorting is important to optimize the use of other algorithms that require sorted lists to work correctly. Sorting has been considered as a fundamental problem in the study of algorithms that due to many reasons namely, the necessary to sort information is inherent in many applications, algorithms often use sorting as a key subroutine, in algorithm design there are many essential techniques represented in the body of sorting algorithms, and many engineering issues come to the fore when implementing sorting algorithms., Many algorithms are very well known for sorting the unordered lists, and one of the well-known algorithms that make the process of sorting to be more economical and efficient is SMS (Scan, Move and Sort) algorithm, an enhancement of Quicksort invented Rami Mansi in 2010. This paper presents a new sorting algorithm called Denni-algorithm. The Denni algorithm is considered as an enhancement on the SMS algorithm in average, and worst cases. The Denni algorithm is compared with the SMS algorithm and the results were promising.

Python algorithms mastering basic algorithms in the Python language

CERN Document Server

Hetland, Magnus Lie

2014-01-01

Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data struc

Optimal Experimental Design of Furan Shock Tube Kinetic Experiments

KAUST Repository

Kim, Daesang

2015-01-07

A Bayesian optimal experimental design methodology has been developed and applied to refine the rate coefficients of elementary reactions in Furan combustion. Furans are considered as potential renewable fuels. We focus on the Arrhenius rates of Furan + OH ↔ Furyl-2 + H2O and Furan ↔ OH Furyl-3 + H2O, and rely on the OH consumption rate as experimental observable. A polynomial chaos surrogate is first constructed using an adaptive pseudo-spectral projection algorithm. The PC surrogate is then exploited in conjunction with a fast estimation of the expected information gain in order to determine the optimal design in the space of initial temperatures and OH concentrations.

Approximation and stability of three-dimensional natural convection flows in a porous medium

International Nuclear Information System (INIS)

Janotto, Marie-Laurence

1991-01-01

The equations of the three-dimensional natural convection in a porous medium within a differentially heated horizontal walls cavity are solved by a pseudo-spectral method. First we will present the evolution of the two main modes according to two models of convection. A few asymptotic properties connected to the small and large eddies are set up and numerically validated. A new approximate inertial manifold is then proposed. The numerical scheme used is an exponential fitting algorithm the convergence of which is proved. We will present the physical mechanism at the origin of the un-stationary three-dimensional convection at high Rayleigh numbers. (author) [fr

Receding Horizon Trajectory Optimization with Terminal Impact Specifications

Directory of Open Access Journals (Sweden)

Limin Zhang

2014-01-01

Full Text Available The trajectory optimization problem subject to terminal impact time and angle specifications can be reformulated as a nonlinear programming problem using the Gauss pseudospectral method. The cost function of the trajectory optimization problem is modified to reduce the terminal control energy. A receding horizon optimization strategy is implemented to reject the errors caused by the motion of a surface target. Several simulations were performed to validate the proposed method via the C programming language. The simulation results demonstrate the effectiveness of the proposed algorithm and that the real-time requirement can be easily achieved if the C programming language is used to realize it.

Hybrid Cryptosystem Using Tiny Encryption Algorithm and LUC Algorithm

Science.gov (United States)

Rachmawati, Dian; Sharif, Amer; Jaysilen; Andri Budiman, Mohammad

2018-01-01

Security becomes a very important issue in data transmission and there are so many methods to make files more secure. One of that method is cryptography. Cryptography is a method to secure file by writing the hidden code to cover the original file. Therefore, if the people do not involve in cryptography, they cannot decrypt the hidden code to read the original file. There are many methods are used in cryptography, one of that method is hybrid cryptosystem. A hybrid cryptosystem is a method that uses a symmetric algorithm to secure the file and use an asymmetric algorithm to secure the symmetric algorithm key. In this research, TEA algorithm is used as symmetric algorithm and LUC algorithm is used as an asymmetric algorithm. The system is tested by encrypting and decrypting the file by using TEA algorithm and using LUC algorithm to encrypt and decrypt the TEA key. The result of this research is by using TEA Algorithm to encrypt the file, the cipher text form is the character from ASCII (American Standard for Information Interchange) table in the form of hexadecimal numbers and the cipher text size increase by sixteen bytes as the plaintext length is increased by eight characters.

Sound algorithms

OpenAIRE

De Götzen , Amalia; Mion , Luca; Tache , Olivier

2007-01-01

International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.

Genetic algorithms

Science.gov (United States)

Wang, Lui; Bayer, Steven E.

1991-01-01

Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

Algorithm aversion: people erroneously avoid algorithms after seeing them err.

Science.gov (United States)

Dietvorst, Berkeley J; Simmons, Joseph P; Massey, Cade

2015-02-01

Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.

The Texas Medication Algorithm Project (TMAP) schizophrenia algorithms.

Science.gov (United States)

Miller, A L; Chiles, J A; Chiles, J K; Crismon, M L; Rush, A J; Shon, S P

1999-10-01

In the Texas Medication Algorithm Project (TMAP), detailed guidelines for medication management of schizophrenia and related disorders, bipolar disorders, and major depressive disorders have been developed and implemented. This article describes the algorithms developed for medication treatment of schizophrenia and related disorders. The guidelines recommend a sequence of medications and discuss dosing, duration, and switch-over tactics. They also specify response criteria at each stage of the algorithm for both positive and negative symptoms. The rationale and evidence for each aspect of the algorithms are presented.

Algorithming the Algorithm

DEFF Research Database (Denmark)

Mahnke, Martina; Uprichard, Emma

2014-01-01

Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...

Pseudo-deterministic Algorithms

OpenAIRE

Goldwasser , Shafi

2012-01-01

International audience; In this talk we describe a new type of probabilistic algorithm which we call Bellagio Algorithms: a randomized algorithm which is guaranteed to run in expected polynomial time, and to produce a correct and unique solution with high probability. These algorithms are pseudo-deterministic: they can not be distinguished from deterministic algorithms in polynomial time by a probabilistic polynomial time observer with black box access to the algorithm. We show a necessary an...

The Algorithmic Imaginary

DEFF Research Database (Denmark)

Bucher, Taina

2017-01-01

the notion of the algorithmic imaginary. It is argued that the algorithmic imaginary – ways of thinking about what algorithms are, what they should be and how they function – is not just productive of different moods and sensations but plays a generative role in moulding the Facebook algorithm itself...... of algorithms affect people's use of these platforms, if at all? To help answer these questions, this article examines people's personal stories about the Facebook algorithm through tweets and interviews with 25 ordinary users. To understand the spaces where people and algorithms meet, this article develops...

An Adaptive Filtering Algorithm Based on Genetic Algorithm-Backpropagation Network

Directory of Open Access Journals (Sweden)

Kai Hu

2013-01-01

Full Text Available A new image filtering algorithm is proposed. GA-BPN algorithm uses genetic algorithm (GA to decide weights in a back propagation neural network (BPN. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-BPN to do image noise filter researching work. Firstly, this paper uses training samples to train GA-BPN as the noise detector. Then, we utilize the well-trained GA-BPN to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-BPN. Experiment data shows that this algorithm has better performance than other filters.

Nature-inspired optimization algorithms

CERN Document Server

Yang, Xin-She

2014-01-01

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning

Convex hull ranking algorithm for multi-objective evolutionary algorithms

NARCIS (Netherlands)

Davoodi Monfrared, M.; Mohades, A.; Rezaei, J.

2012-01-01

Due to many applications of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent years. Since most multi-objective evolutionary algorithms are based on the non-dominated principle, and their complexity

Total algorithms

NARCIS (Netherlands)

Tel, G.

We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of

Computer Aided Analysis of TM-Multimode Planar Graded-index Optical Waveguides

International Nuclear Information System (INIS)

Ashry, M.; Nasr, A.S.; Abou El-Fadl, A.A.

2000-01-01

An algorithm is developed for analysis TM-Multimode Planar graded-index optical waveguides. A Modified Impedance Boundary Method of Moments (MIBMOM) for the analysis of planar graded-index optical waveguide structures is presented. The algorithm is used to calculate the dispersion characteristics and the field distribution of TM-multimode planar graded-index optical waveguides. The technique is based on Galerkin s procedure and the exact boundary condition at the interfaces between the graded index region and the step index cladding. Legendre polynomials are used as basis functions. The efficiency of this algorithm is examined with waveguides having various index profiles such as exponential, Gaussian and complementary error functions. The advantage of the MIBMOM is the complete solution of TM-multimode as presented which is very difficult by the other methods. With this algorithm a minimum number of basis functions to give accurate results is used. The obtained results show good agreement with the experimental results

Progressive geometric algorithms

NARCIS (Netherlands)

Alewijnse, S.P.A.; Bagautdinov, T.M.; de Berg, M.T.; Bouts, Q.W.; ten Brink, Alex P.; Buchin, K.A.; Westenberg, M.A.

2015-01-01

Progressive algorithms are algorithms that, on the way to computing a complete solution to the problem at hand, output intermediate solutions that approximate the complete solution increasingly well. We present a framework for analyzing such algorithms, and develop efficient progressive algorithms

Progressive geometric algorithms

NARCIS (Netherlands)

Alewijnse, S.P.A.; Bagautdinov, T.M.; Berg, de M.T.; Bouts, Q.W.; Brink, ten A.P.; Buchin, K.; Westenberg, M.A.

2014-01-01

Progressive algorithms are algorithms that, on the way to computing a complete solution to the problem at hand, output intermediate solutions that approximate the complete solution increasingly well. We present a framework for analyzing such algorithms, and develop efficient progressive algorithms

Archimedean copula estimation of distribution algorithm based on artificial bee colony algorithm

Institute of Scientific and Technical Information of China (English)

Haidong Xu; Mingyan Jiang; Kun Xu

2015-01-01

The artificial bee colony (ABC) algorithm is a com-petitive stochastic population-based optimization algorithm. How-ever, the ABC algorithm does not use the social information and lacks the knowledge of the problem structure, which leads to in-sufficiency in both convergent speed and searching precision. Archimedean copula estimation of distribution algorithm (ACEDA) is a relatively simple, time-economic and multivariate correlated EDA. This paper proposes a novel hybrid algorithm based on the ABC algorithm and ACEDA cal ed Archimedean copula estima-tion of distribution based on the artificial bee colony (ACABC) algorithm. The hybrid algorithm utilizes ACEDA to estimate the distribution model and then uses the information to help artificial bees to search more efficiently in the search space. Six bench-mark functions are introduced to assess the performance of the ACABC algorithm on numerical function optimization. Experimen-tal results show that the ACABC algorithm converges much faster with greater precision compared with the ABC algorithm, ACEDA and the global best (gbest)-guided ABC (GABC) algorithm in most of the experiments.

A filtered backprojection algorithm with characteristics of the iterative landweber algorithm

OpenAIRE

L. Zeng, Gengsheng

2012-01-01

Purpose: In order to eventually develop an analytical algorithm with noise characteristics of an iterative algorithm, this technical note develops a window function for the filtered backprojection (FBP) algorithm in tomography that behaves as an iterative Landweber algorithm.

Combinatorial interpretations of particular evaluations of complete and elementary symmetric functions

OpenAIRE

Mongelli, Pietro

2011-01-01

The Jacobi-Stirling numbers and the Legendre-Stirling numbers of the first and second kind were first introduced in [6], [7]. In this paper we note that Jacobi-Stirling numbers and Legendre-Stirling numbers are specializations of elementary and complete symmetric functions. We then study combinatorial interpretations of this specialization and obtain new combinatorial interpretations of the Jacobi-Stirling and Legendre-Stirling numbers.

Super-Encryption Implementation Using Monoalphabetic Algorithm and XOR Algorithm for Data Security

Science.gov (United States)

Rachmawati, Dian; Andri Budiman, Mohammad; Aulia, Indra

2018-03-01

The exchange of data that occurs offline and online is very vulnerable to the threat of data theft. In general, cryptography is a science and art to maintain data secrecy. An encryption is a cryptography algorithm in which data is transformed into cipher text, which is something that is unreadable and meaningless so it cannot be read or understood by other parties. In super-encryption, two or more encryption algorithms are combined to make it more secure. In this work, Monoalphabetic algorithm and XOR algorithm are combined to form a super- encryption. Monoalphabetic algorithm works by changing a particular letter into a new letter based on existing keywords while the XOR algorithm works by using logic operation XOR Since Monoalphabetic algorithm is a classical cryptographic algorithm and XOR algorithm is a modern cryptographic algorithm, this scheme is expected to be both easy-to-implement and more secure. The combination of the two algorithms is capable of securing the data and restoring it back to its original form (plaintext), so the data integrity is still ensured.

Linear feature detection algorithm for astronomical surveys - I. Algorithm description

Science.gov (United States)

Bektešević, Dino; Vinković, Dejan

2017-11-01

Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.

Golden Sine Algorithm: A Novel Math-Inspired Algorithm

Directory of Open Access Journals (Sweden)

TANYILDIZI, E.

2017-05-01

Full Text Available In this study, Golden Sine Algorithm (Gold-SA is presented as a new metaheuristic method for solving optimization problems. Gold-SA has been developed as a new search algorithm based on population. This math-based algorithm is inspired by sine that is a trigonometric function. In the algorithm, random individuals are created as many as the number of search agents with uniform distribution for each dimension. The Gold-SA operator searches to achieve a better solution in each iteration by trying to bring the current situation closer to the target value. The solution space is narrowed by the golden section so that the areas that are supposed to give only good results are scanned instead of the whole solution space scan. In the tests performed, it is seen that Gold-SA has better results than other population based methods. In addition, Gold-SA has fewer algorithm-dependent parameters and operators than other metaheuristic methods, increasing the importance of this method by providing faster convergence of this new method.

The Orthogonally Partitioned EM Algorithm: Extending the EM Algorithm for Algorithmic Stability and Bias Correction Due to Imperfect Data.

Science.gov (United States)

Regier, Michael D; Moodie, Erica E M

2016-05-01

We propose an extension of the EM algorithm that exploits the common assumption of unique parameterization, corrects for biases due to missing data and measurement error, converges for the specified model when standard implementation of the EM algorithm has a low probability of convergence, and reduces a potentially complex algorithm into a sequence of smaller, simpler, self-contained EM algorithms. We use the theory surrounding the EM algorithm to derive the theoretical results of our proposal, showing that an optimal solution over the parameter space is obtained. A simulation study is used to explore the finite sample properties of the proposed extension when there is missing data and measurement error. We observe that partitioning the EM algorithm into simpler steps may provide better bias reduction in the estimation of model parameters. The ability to breakdown a complicated problem in to a series of simpler, more accessible problems will permit a broader implementation of the EM algorithm, permit the use of software packages that now implement and/or automate the EM algorithm, and make the EM algorithm more accessible to a wider and more general audience.

Parallel sorting algorithms

CERN Document Server

Akl, Selim G

1985-01-01

Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the

Trajectory Optimization Based on Multi-Interval Mesh Refinement Method

Directory of Open Access Journals (Sweden)

Ningbo Li

2017-01-01

Full Text Available In order to improve the optimization accuracy and convergence rate for trajectory optimization of the air-to-air missile, a multi-interval mesh refinement Radau pseudospectral method was introduced. This method made the mesh endpoints converge to the practical nonsmooth points and decreased the overall collocation points to improve convergence rate and computational efficiency. The trajectory was divided into four phases according to the working time of engine and handover of midcourse and terminal guidance, and then the optimization model was built. The multi-interval mesh refinement Radau pseudospectral method with different collocation points in each mesh interval was used to solve the trajectory optimization model. Moreover, this method was compared with traditional h method. Simulation results show that this method can decrease the dimensionality of nonlinear programming (NLP problem and therefore improve the efficiency of pseudospectral methods for solving trajectory optimization problems.

Fermion cluster algorithms

International Nuclear Information System (INIS)

Chandrasekharan, Shailesh

2000-01-01

Cluster algorithms have been recently used to eliminate sign problems that plague Monte-Carlo methods in a variety of systems. In particular such algorithms can also be used to solve sign problems associated with the permutation of fermion world lines. This solution leads to the possibility of designing fermion cluster algorithms in certain cases. Using the example of free non-relativistic fermions we discuss the ideas underlying the algorithm

Algorithm improvement program nuclide identification algorithm scoring criteria and scoring application.

Energy Technology Data Exchange (ETDEWEB)

Enghauser, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-02-01

The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.

Algorithm of Particle Data Association for SLAM Based on Improved Ant Algorithm

Directory of Open Access Journals (Sweden)

KeKe Gen

2015-01-01

Full Text Available The article considers a problem of data association algorithm for simultaneous localization and mapping guidelines in determining the route of unmanned aerial vehicles (UAVs. Currently, these equipments are already widely used, but mainly controlled from the remote operator. An urgent task is to develop a control system that allows for autonomous flight. Algorithm SLAM (simultaneous localization and mapping, which allows to predict the location, speed, the ratio of flight parameters and the coordinates of landmarks and obstacles in an unknown environment, is one of the key technologies to achieve real autonomous UAV flight. The aim of this work is to study the possibility of solving this problem by using an improved ant algorithm.The data association for SLAM algorithm is meant to establish a matching set of observed landmarks and landmarks in the state vector. Ant algorithm is one of the widely used optimization algorithms with positive feedback and the ability to search in parallel, so the algorithm is suitable for solving the problem of data association for SLAM. But the traditional ant algorithm in the process of finding routes easily falls into local optimum. Adding random perturbations in the process of updating the global pheromone to avoid local optima. Setting limits pheromone on the route can increase the search space with a reasonable amount of calculations for finding the optimal route.The paper proposes an algorithm of the local data association for SLAM algorithm based on an improved ant algorithm. To increase the speed of calculation, local data association is used instead of the global data association. The first stage of the algorithm defines targets in the matching space and the observed landmarks with the possibility of association by the criterion of individual compatibility (IC. The second stage defines the matched landmarks and their coordinates using improved ant algorithm. Simulation results confirm the efficiency and

The BR eigenvalue algorithm

Energy Technology Data Exchange (ETDEWEB)

Geist, G.A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Howell, G.W. [Florida Inst. of Tech., Melbourne, FL (United States). Dept. of Applied Mathematics; Watkins, D.S. [Washington State Univ., Pullman, WA (United States). Dept. of Pure and Applied Mathematics

1997-11-01

The BR algorithm, a new method for calculating the eigenvalues of an upper Hessenberg matrix, is introduced. It is a bulge-chasing algorithm like the QR algorithm, but, unlike the QR algorithm, it is well adapted to computing the eigenvalues of the narrowband, nearly tridiagonal matrices generated by the look-ahead Lanczos process. This paper describes the BR algorithm and gives numerical evidence that it works well in conjunction with the Lanczos process. On the biggest problems run so far, the BR algorithm beats the QR algorithm by a factor of 30--60 in computing time and a factor of over 100 in matrix storage space.

Geometric approximation algorithms

CERN Document Server

Har-Peled, Sariel

2011-01-01

Exact algorithms for dealing with geometric objects are complicated, hard to implement in practice, and slow. Over the last 20 years a theory of geometric approximation algorithms has emerged. These algorithms tend to be simple, fast, and more robust than their exact counterparts. This book is the first to cover geometric approximation algorithms in detail. In addition, more traditional computational geometry techniques that are widely used in developing such algorithms, like sampling, linear programming, etc., are also surveyed. Other topics covered include approximate nearest-neighbor search, shape approximation, coresets, dimension reduction, and embeddings. The topics covered are relatively independent and are supplemented by exercises. Close to 200 color figures are included in the text to illustrate proofs and ideas.

Algorithms in Singular

Directory of Open Access Journals (Sweden)

Hans Schonemann

1996-12-01

Full Text Available Some algorithms for singularity theory and algebraic geometry The use of Grobner basis computations for treating systems of polynomial equations has become an important tool in many areas. This paper introduces of the concept of standard bases (a generalization of Grobner bases and the application to some problems from algebraic geometry. The examples are presented as SINGULAR commands. A general introduction to Grobner bases can be found in the textbook [CLO], an introduction to syzygies in [E] and [St1]. SINGULAR is a computer algebra system for computing information about singularities, for use in algebraic geometry. The basic algorithms in SINGULAR are several variants of a general standard basis algorithm for general monomial orderings (see [GG]. This includes wellorderings (Buchberger algorithm ([B1], [B2] and tangent cone orderings (Mora algorithm ([M1], [MPT] as special cases: It is able to work with non-homogeneous and homogeneous input and also to compute in the localization of the polynomial ring in 0. Recent versions include algorithms to factorize polynomials and a factorizing Grobner basis algorithm. For a complete description of SINGULAR see [Si].

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

Science.gov (United States)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

Modified Firefly Algorithm

Directory of Open Access Journals (Sweden)

Surafel Luleseged Tilahun

2012-01-01

Full Text Available Firefly algorithm is one of the new metaheuristic algorithms for optimization problems. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be considered as fireflies, and brightness is assigned depending on their performance on the objective function. One of the rules used to construct the algorithm is, a firefly will be attracted to a brighter firefly, and if there is no brighter firefly, it will move randomly. In this paper we modify this random movement of the brighter firefly by generating random directions in order to determine the best direction in which the brightness increases. If such a direction is not generated, it will remain in its current position. Furthermore the assignment of attractiveness is modified in such a way that the effect of the objective function is magnified. From the simulation result it is shown that the modified firefly algorithm performs better than the standard one in finding the best solution with smaller CPU time.

Network-Oblivious Algorithms

DEFF Research Database (Denmark)

Bilardi, Gianfranco; Pietracaprina, Andrea; Pucci, Geppino

2016-01-01

A framework is proposed for the design and analysis of network-oblivious algorithms, namely algorithms that can run unchanged, yet efficiently, on a variety of machines characterized by different degrees of parallelism and communication capabilities. The framework prescribes that a network......-oblivious algorithm be specified on a parallel model of computation where the only parameter is the problem’s input size, and then evaluated on a model with two parameters, capturing parallelism granularity and communication latency. It is shown that for a wide class of network-oblivious algorithms, optimality...... of cache hierarchies, to the realm of parallel computation. Its effectiveness is illustrated by providing optimal network-oblivious algorithms for a number of key problems. Some limitations of the oblivious approach are also discussed....

Efficient scheme for parametric fitting of data in arbitrary dimensions.

Science.gov (United States)

Pang, Ning-Ning; Tzeng, Wen-Jer; Kao, Hisen-Ching

2008-07-01

We propose an efficient scheme for parametric fitting expressed in terms of the Legendre polynomials. For continuous systems, our scheme is exact and the derived explicit expression is very helpful for further analytical studies. For discrete systems, our scheme is almost as accurate as the method of singular value decomposition. Through a few numerical examples, we show that our algorithm costs much less CPU time and memory space than the method of singular value decomposition. Thus, our algorithm is very suitable for a large amount of data fitting. In addition, the proposed scheme can also be used to extract the global structure of fluctuating systems. We then derive the exact relation between the correlation function and the detrended variance function of fluctuating systems in arbitrary dimensions and give a general scaling analysis.

A novel hybrid algorithm of GSA with Kepler algorithm for numerical optimization

Directory of Open Access Journals (Sweden)

Soroor Sarafrazi

2015-07-01

Full Text Available It is now well recognized that pure algorithms can be promisingly improved by hybridization with other techniques. One of the relatively new metaheuristic algorithms is Gravitational Search Algorithm (GSA which is based on the Newton laws. In this paper, to enhance the performance of GSA, a novel algorithm called “Kepler”, inspired by the astrophysics, is introduced. The Kepler algorithm is based on the principle of the first Kepler law. The hybridization of GSA and Kepler algorithm is an efficient approach to provide much stronger specialization in intensification and/or diversification. The performance of GSA–Kepler is evaluated by applying it to 14 benchmark functions with 20–1000 dimensions and the optimal approximation of linear system as a practical optimization problem. The results obtained reveal that the proposed hybrid algorithm is robust enough to optimize the benchmark functions and practical optimization problems.

Algorithmically specialized parallel computers

CERN Document Server

Snyder, Lawrence; Gannon, Dennis B

1985-01-01

Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster

DEVELOPMENT OF A NEW ALGORITHM FOR KEY AND S-BOX GENERATION IN BLOWFISH ALGORITHM

Directory of Open Access Journals (Sweden)

TAYSEER S. ATIA

2014-08-01

Full Text Available Blowfish algorithm is a block cipher algorithm, its strong, simple algorithm used to encrypt data in block of size 64-bit. Key and S-box generation process in this algorithm require time and memory space the reasons that make this algorithm not convenient to be used in smart card or application requires changing secret key frequently. In this paper a new key and S-box generation process was developed based on Self Synchronization Stream Cipher (SSS algorithm where the key generation process for this algorithm was modified to be used with the blowfish algorithm. Test result shows that the generation process requires relatively slow time and reasonably low memory requirement and this enhance the algorithm and gave it the possibility for different usage.

Monte Carlo algorithms with absorbing Markov chains: Fast local algorithms for slow dynamics

International Nuclear Information System (INIS)

Novotny, M.A.

1995-01-01

A class of Monte Carlo algorithms which incorporate absorbing Markov chains is presented. In a particular limit, the lowest order of these algorithms reduces to the n-fold way algorithm. These algorithms are applied to study the escape from the metastable state in the two-dimensional square-lattice nearest-neighbor Ising ferromagnet in an unfavorable applied field, and the agreement with theoretical predictions is very good. It is demonstrated that the higher-order algorithms can be many orders of magnitude faster than either the traditional Monte Carlo or n-fold way algorithms

Dynamic route guidance algorithm based algorithm based on artificial immune system

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

To improve the performance of the K-shortest paths search in intelligent traffic guidance systems,this paper proposes an optimal search algorithm based on the intelligent optimization search theory and the memphor mechanism of vertebrate immune systems.This algorithm,applied to the urban traffic network model established by the node-expanding method,can expediently realize K-shortest paths search in the urban traffic guidance systems.Because of the immune memory and global parallel search ability from artificial immune systems,K shortest paths can be found without any repeat,which indicates evidently the superiority of the algorithm to the conventional ones.Not only does it perform a better parallelism,the algorithm also prevents premature phenomenon that often occurs in genetic algorithms.Thus,it is especially suitable for real-time requirement of the traffic guidance system and other engineering optimal applications.A case study verifies the efficiency and the practicability of the algorithm aforementioned.

Electric drill-string telemetry

CERN Document Server

Carcione, J M

2003-01-01

We design a numerical algorithm for simulation of low-frequency electric-signal transmission through a drill string. This is represented by a transmission line with varying geometrical and electromagnetic properties versus depth, depending on the characteristics of the drill-string/formation system. These properties are implicitly modeled by the series impedance and the shunt admittance of the transmission line. The differential equations are parabolic, since at low frequencies the wave field is diffusive. We use an explicit scheme for the solution of parabolic problems, based on a Chebyshev expansion of the evolution operator and the Fourier pseudospectral method to compute the spatial derivatives. The results are verified by comparison to analytical solutions obtained for the initial-value problem with a voltage source.

Definite Integrals using Orthogonality and Integral Transforms

Directory of Open Access Journals (Sweden)

Howard S. Cohl

2012-10-01

Full Text Available We obtain definite integrals for products of associated Legendre functions with Bessel functions, associated Legendre functions, and Chebyshev polynomials of the first kind using orthogonality and integral transforms.

Hamiltonian Algorithm Sound Synthesis

OpenAIRE

大矢, 健一

2013-01-01

Hamiltonian Algorithm (HA) is an algorithm for searching solutions is optimization problems. This paper introduces a sound synthesis technique using Hamiltonian Algorithm and shows a simple example. "Hamiltonian Algorithm Sound Synthesis" uses phase transition effect in HA. Because of this transition effect, totally new waveforms are produced.

Modified Clipped LMS Algorithm

Directory of Open Access Journals (Sweden)

Lotfizad Mojtaba

2005-01-01

Full Text Available Abstract A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.

Algorithms as fetish: Faith and possibility in algorithmic work

Directory of Open Access Journals (Sweden)

Suzanne L Thomas

2018-01-01

Full Text Available Algorithms are powerful because we invest in them the power to do things. With such promise, they can transform the ordinary, say snapshots along a robotic vacuum cleaner’s route, into something much more, such as a clean home. Echoing David Graeber’s revision of fetishism, we argue that this easy slip from technical capabilities to broader claims betrays not the “magic” of algorithms but rather the dynamics of their exchange. Fetishes are not indicators of false thinking, but social contracts in material form. They mediate emerging distributions of power often too nascent, too slippery or too disconcerting to directly acknowledge. Drawing primarily on 2016 ethnographic research with computer vision professionals, we show how faith in what algorithms can do shapes the social encounters and exchanges of their production. By analyzing algorithms through the lens of fetishism, we can see the social and economic investment in some people’s labor over others. We also see everyday opportunities for social creativity and change. We conclude that what is problematic about algorithms is not their fetishization but instead their stabilization into full-fledged gods and demons – the more deserving objects of critique.

Quick fuzzy backpropagation algorithm.

Science.gov (United States)

Nikov, A; Stoeva, S

2001-03-01

A modification of the fuzzy backpropagation (FBP) algorithm called QuickFBP algorithm is proposed, where the computation of the net function is significantly quicker. It is proved that the FBP algorithm is of exponential time complexity, while the QuickFBP algorithm is of polynomial time complexity. Convergence conditions of the QuickFBP, resp. the FBP algorithm are defined and proved for: (1) single output neural networks in case of training patterns with different targets; and (2) multiple output neural networks in case of training patterns with equivalued target vector. They support the automation of the weights training process (quasi-unsupervised learning) establishing the target value(s) depending on the network's input values. In these cases the simulation results confirm the convergence of both algorithms. An example with a large-sized neural network illustrates the significantly greater training speed of the QuickFBP rather than the FBP algorithm. The adaptation of an interactive web system to users on the basis of the QuickFBP algorithm is presented. Since the QuickFBP algorithm ensures quasi-unsupervised learning, this implies its broad applicability in areas of adaptive and adaptable interactive systems, data mining, etc. applications.

A New Modified Firefly Algorithm

Directory of Open Access Journals (Sweden)

Medha Gupta

2016-07-01

Full Text Available Nature inspired meta-heuristic algorithms studies the emergent collective intelligence of groups of simple agents. Firefly Algorithm is one of the new such swarm-based metaheuristic algorithm inspired by the flashing behavior of fireflies. The algorithm was first proposed in 2008 and since then has been successfully used for solving various optimization problems. In this work, we intend to propose a new modified version of Firefly algorithm (MoFA and later its performance is compared with the standard firefly algorithm along with various other meta-heuristic algorithms. Numerical studies and results demonstrate that the proposed algorithm is superior to existing algorithms.

Quantum Computation and Algorithms

International Nuclear Information System (INIS)

Biham, O.; Biron, D.; Biham, E.; Grassi, M.; Lidar, D.A.

1999-01-01

It is now firmly established that quantum algorithms provide a substantial speedup over classical algorithms for a variety of problems, including the factorization of large numbers and the search for a marked element in an unsorted database. In this talk I will review the principles of quantum algorithms, the basic quantum gates and their operation. The combination of superposition and interference, that makes these algorithms efficient, will be discussed. In particular, Grover's search algorithm will be presented as an example. I will show that the time evolution of the amplitudes in Grover's algorithm can be found exactly using recursion equations, for any initial amplitude distribution

Semioptimal practicable algorithmic cooling

International Nuclear Information System (INIS)

Elias, Yuval; Mor, Tal; Weinstein, Yossi

2011-01-01

Algorithmic cooling (AC) of spins applies entropy manipulation algorithms in open spin systems in order to cool spins far beyond Shannon's entropy bound. Algorithmic cooling of nuclear spins was demonstrated experimentally and may contribute to nuclear magnetic resonance spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semioptimal practicable AC (SOPAC), wherein a few cycles (typically two to six) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC and are much more efficient than the exhaustive algorithms. These algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.

An Ordering Linear Unification Algorithm

Institute of Scientific and Technical Information of China (English)

胡运发

1989-01-01

In this paper,we present an ordering linear unification algorithm(OLU).A new idea on substituteion of the binding terms is introduced to the algorithm,which is able to overcome some drawbacks of other algorithms,e.g.,MM algorithm[1],RG1 and RG2 algorithms[2],Particularly,if we use the directed eyclie graphs,the algoritm needs not check the binding order,then the OLU algorithm can also be aplied to the infinite tree data struceture,and a higher efficiency can be expected.The paper focuses upon the discussion of OLU algorithm and a partial order structure with respect to the unification algorithm.This algorithm has been implemented in the GKD-PROLOG/VAX 780 interpreting system.Experimental results have shown that the algorithm is very simple and efficient.

Normalization of Gravitational Acceleration Models

Science.gov (United States)

Eckman, Randy A.; Brown, Aaron J.; Adamo, Daniel R.

2011-01-01

Unlike the uniform density spherical shell approximations of Newton, the con- sequence of spaceflight in the real universe is that gravitational fields are sensitive to the nonsphericity of their generating central bodies. The gravitational potential of a nonspherical central body is typically resolved using spherical harmonic approximations. However, attempting to directly calculate the spherical harmonic approximations results in at least two singularities which must be removed in order to generalize the method and solve for any possible orbit, including polar orbits. Three unique algorithms have been developed to eliminate these singularities by Samuel Pines [1], Bill Lear [2], and Robert Gottlieb [3]. This paper documents the methodical normalization of two1 of the three known formulations for singularity-free gravitational acceleration (namely, the Lear [2] and Gottlieb [3] algorithms) and formulates a general method for defining normalization parameters used to generate normalized Legendre Polynomials and ALFs for any algorithm. A treatment of the conventional formulation of the gravitational potential and acceleration is also provided, in addition to a brief overview of the philosophical differences between the three known singularity-free algorithms.

Recent developments for the pattern recognition in the central drift chamber of the Belle II detector

Energy Technology Data Exchange (ETDEWEB)

Trusov, Viktor; Feindt, Michael; Heck, Martin; Hauth, Thomas; Goldenzweig, Pablo [Karlsruhe Institute of Technology (Germany); Collaboration: Belle II-Collaboration

2016-07-01

The Belle II experiment is designed to perform more precise measurements (e.g. C P-violation measurements, New Physics phenomena, rare decays etc) than its predecessor, the Belle experiment. To achieve this goal, the luminosity of the experiment will be increased by a factor of 40 and as result multiple times more data will be collected. Due to this fact, faster reconstruction algorithms for the data processing need to be developed and at the same time accurate physical results should be retained. One important part in the data processing chain is the track reconstruction section. We present the development of one of the pattern recognition algorithms for the Belle II experiment based on conformal and Legendre transformations. In order to optimize the performance of the algorithm (CPU time and efficiency) we have introduced specialized processing steps. To show improvements in the results we introduce efficiency measurements of the tracking algorithms in the Central Drift Chamber (CDC) which were done using Monte-Carlo simulation of e{sup +} e{sup -} collisions followed by a full simulation of the Belle II detector.

Chebfun and numerical quadrature

KAUST Repository

Hale, Nicholas; Trefethen, Lloyd N.

2012-01-01

Chebfun is a Matlab-based software system that overloads Matlab's discrete operations for vectors and matrices to analogous continuous operations for functions and operators. We begin by describing Chebfun's fast capabilities for Clenshaw-Curtis and also Gauss-Legendre, -Jacobi, -Hermite, and -Laguerre quadrature, based on algorithms of Waldvogel and Glaser, Liu and Rokhlin. Then we consider how such methods can be applied to quadrature problems including 2D integrals over rectangles, fractional derivatives and integrals, functions defined on unbounded intervals, and the fast computation of weights for barycentric interpolation. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.

Chebfun and numerical quadrature

KAUST Repository

Hale, Nicholas

2012-07-24

Chebfun is a Matlab-based software system that overloads Matlab\\'s discrete operations for vectors and matrices to analogous continuous operations for functions and operators. We begin by describing Chebfun\\'s fast capabilities for Clenshaw-Curtis and also Gauss-Legendre, -Jacobi, -Hermite, and -Laguerre quadrature, based on algorithms of Waldvogel and Glaser, Liu and Rokhlin. Then we consider how such methods can be applied to quadrature problems including 2D integrals over rectangles, fractional derivatives and integrals, functions defined on unbounded intervals, and the fast computation of weights for barycentric interpolation. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.

VISUALIZATION OF PAGERANK ALGORITHM

OpenAIRE

Perhaj, Ervin

2013-01-01

The goal of the thesis is to develop a web application that help users understand the functioning of the PageRank algorithm. The thesis consists of two parts. First we develop an algorithm to calculate PageRank values of web pages. The input of algorithm is a list of web pages and links between them. The user enters the list through the web interface. From the data the algorithm calculates PageRank value for each page. The algorithm repeats the process, until the difference of PageRank va...

RFID Location Algorithm

Directory of Open Access Journals (Sweden)

Wang Zi Min

2016-01-01

Full Text Available With the development of social services, people’s living standards improve further requirements, there is an urgent need for a way to adapt to the complex situation of the new positioning technology. In recent years, RFID technology have a wide range of applications in all aspects of life and production, such as logistics tracking, car alarm, security and other items. The use of RFID technology to locate, it is a new direction in the eyes of the various research institutions and scholars. RFID positioning technology system stability, the error is small and low-cost advantages of its location algorithm is the focus of this study.This article analyzes the layers of RFID technology targeting methods and algorithms. First, RFID common several basic methods are introduced; Secondly, higher accuracy to political network location method; Finally, LANDMARC algorithm will be described. Through this it can be seen that advanced and efficient algorithms play an important role in increasing RFID positioning accuracy aspects.Finally, the algorithm of RFID location technology are summarized, pointing out the deficiencies in the algorithm, and put forward a follow-up study of the requirements, the vision of a better future RFID positioning technology.

Improved multivariate polynomial factoring algorithm

International Nuclear Information System (INIS)

Wang, P.S.

1978-01-01

A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timing are included

Governance by algorithms

Directory of Open Access Journals (Sweden)

Francesca Musiani

2013-08-01

Full Text Available Algorithms are increasingly often cited as one of the fundamental shaping devices of our daily, immersed-in-information existence. Their importance is acknowledged, their performance scrutinised in numerous contexts. Yet, a lot of what constitutes 'algorithms' beyond their broad definition as “encoded procedures for transforming input data into a desired output, based on specified calculations” (Gillespie, 2013 is often taken for granted. This article seeks to contribute to the discussion about 'what algorithms do' and in which ways they are artefacts of governance, providing two examples drawing from the internet and ICT realm: search engine queries and e-commerce websites’ recommendations to customers. The question of the relationship between algorithms and rules is likely to occupy an increasingly central role in the study and the practice of internet governance, in terms of both institutions’ regulation of algorithms, and algorithms’ regulation of our society.

Algorithmic and user study of an autocompletion algorithm on a large medical vocabulary.

Science.gov (United States)

Sevenster, Merlijn; van Ommering, Rob; Qian, Yuechen

2012-02-01

Autocompletion supports human-computer interaction in software applications that let users enter textual data. We will be inspired by the use case in which medical professionals enter ontology concepts, catering the ongoing demand for structured and standardized data in medicine. Goal is to give an algorithmic analysis of one particular autocompletion algorithm, called multi-prefix matching algorithm, which suggests terms whose words' prefixes contain all words in the string typed by the user, e.g., in this sense, opt ner me matches optic nerve meningioma. Second we aim to investigate how well it supports users entering concepts from a large and comprehensive medical vocabulary (snomed ct). We give a concise description of the multi-prefix algorithm, and sketch how it can be optimized to meet required response time. Performance will be compared to a baseline algorithm, which gives suggestions that extend the string typed by the user to the right, e.g. optic nerve m gives optic nerve meningioma, but opt ner me does not. We conduct a user experiment in which 12 participants are invited to complete 40 snomed ct terms with the baseline algorithm and another set of 40 snomed ct terms with the multi-prefix algorithm. Our results show that users need significantly fewer keystrokes when supported by the multi-prefix algorithm than when supported by the baseline algorithm. The proposed algorithm is a competitive candidate for searching and retrieving terms from a large medical ontology. Copyright © 2011 Elsevier Inc. All rights reserved.

Optimal Fungal Space Searching Algorithms.

Science.gov (United States)

Asenova, Elitsa; Lin, Hsin-Yu; Fu, Eileen; Nicolau, Dan V; Nicolau, Dan V

2016-10-01

Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies.

A stabilized Runge–Kutta–Legendre method for explicit super-time-stepping of parabolic and mixed equations

International Nuclear Information System (INIS)

Meyer, Chad D.; Balsara, Dinshaw S.; Aslam, Tariq D.

2014-01-01

Parabolic partial differential equations appear in several physical problems, including problems that have a dominant hyperbolic part coupled to a sub-dominant parabolic component. Explicit methods for their solution are easy to implement but have very restrictive time step constraints. Implicit solution methods can be unconditionally stable but have the disadvantage of being computationally costly or difficult to implement. Super-time-stepping methods for treating parabolic terms in mixed type partial differential equations occupy an intermediate position. In such methods each superstep takes “s” explicit Runge–Kutta-like time-steps to advance the parabolic terms by a time-step that is s 2 times larger than a single explicit time-step. The expanded stability is usually obtained by mapping the short recursion relation of the explicit Runge–Kutta scheme to the recursion relation of some well-known, stable polynomial. Prior work has built temporally first- and second-order accurate super-time-stepping methods around the recursion relation associated with Chebyshev polynomials. Since their stability is based on the boundedness of the Chebyshev polynomials, these methods have been called RKC1 and RKC2. In this work we build temporally first- and second-order accurate super-time-stepping methods around the recursion relation associated with Legendre polynomials. We call these methods RKL1 and RKL2. The RKL1 method is first-order accurate in time; the RKL2 method is second-order accurate in time. We verify that the newly-designed RKL1 and RKL2 schemes have a very desirable monotonicity preserving property for one-dimensional problems – a solution that is monotone at the beginning of a time step retains that property at the end of that time step. It is shown that RKL1 and RKL2 methods are stable for all values of the diffusion coefficient up to the maximum value. We call this a convex monotonicity preserving property and show by examples that it is very useful

Autonomous Star Tracker Algorithms

DEFF Research Database (Denmark)

Betto, Maurizio; Jørgensen, John Leif; Kilsgaard, Søren

1998-01-01

Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances.......Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances....

Entropy Stable Staggered Grid Discontinuous Spectral Collocation Methods of any Order for the Compressible Navier--Stokes Equations

KAUST Repository

Parsani, Matteo; Carpenter, Mark H.; Fisher, Travis C.; Nielsen, Eric J.

2016-01-01

set of points from tensor product, Legendre--Gauss--Lobatto (LGL), to a combination of tensor product Legendre--Gauss (LG) and LGL points. The new semidiscrete operators discretely conserve mass, momentum, energy, and satisfy a mathematical entropy

Fast geometric algorithms

International Nuclear Information System (INIS)

Noga, M.T.

1984-01-01

This thesis addresses a number of important problems that fall within the framework of the new discipline of Computational Geometry. The list of topics covered includes sorting and selection, convex hull algorithms, the L 1 hull, determination of the minimum encasing rectangle of a set of points, the Euclidean and L 1 diameter of a set of points, the metric traveling salesman problem, and finding the superrange of star-shaped and monotype polygons. The main theme of all the work was to develop a set of very fast state-of-the-art algorithms that supersede any rivals in terms of speed and ease of implementation. In some cases existing algorithms were refined; for others new techniques were developed that add to the present database of fast adaptive geometric algorithms. What emerges is a collection of techniques that is successful at merging modern tools developed in analysis of algorithms with those of classical geometry

Genetic Algorithm Applied to the Eigenvalue Equalization Filtered-x LMS Algorithm (EE-FXLMS

Directory of Open Access Journals (Sweden)

Stephan P. Lovstedt

2008-01-01

Full Text Available The FXLMS algorithm, used extensively in active noise control (ANC, exhibits frequency-dependent convergence behavior. This leads to degraded performance for time-varying tonal noise and noise with multiple stationary tones. Previous work by the authors proposed the eigenvalue equalization filtered-x least mean squares (EE-FXLMS algorithm. For that algorithm, magnitude coefficients of the secondary path transfer function are modified to decrease variation in the eigenvalues of the filtered-x autocorrelation matrix, while preserving the phase, giving faster convergence and increasing overall attenuation. This paper revisits the EE-FXLMS algorithm, using a genetic algorithm to find magnitude coefficients that give the least variation in eigenvalues. This method overcomes some of the problems with implementing the EE-FXLMS algorithm arising from finite resolution of sampled systems. Experimental control results using the original secondary path model, and a modified secondary path model for both the previous implementation of EE-FXLMS and the genetic algorithm implementation are compared.

On factoring RSA modulus using random-restart hill-climbing algorithm and Pollard’s rho algorithm

Science.gov (United States)

Budiman, M. A.; Rachmawati, D.

2017-12-01

The security of the widely-used RSA public key cryptography algorithm depends on the difficulty of factoring a big integer into two large prime numbers. For many years, the integer factorization problem has been intensively and extensively studied in the field of number theory. As a result, a lot of deterministic algorithms such as Euler’s algorithm, Kraitchik’s, and variants of Pollard’s algorithms have been researched comprehensively. Our study takes a rather uncommon approach: rather than making use of intensive number theories, we attempt to factorize RSA modulus n by using random-restart hill-climbing algorithm, which belongs the class of metaheuristic algorithms. The factorization time of RSA moduli with different lengths is recorded and compared with the factorization time of Pollard’s rho algorithm, which is a deterministic algorithm. Our experimental results indicates that while random-restart hill-climbing algorithm is an acceptable candidate to factorize smaller RSA moduli, the factorization speed is much slower than that of Pollard’s rho algorithm.

Opposition-Based Adaptive Fireworks Algorithm

Directory of Open Access Journals (Sweden)

Chibing Gong

2016-07-01

Full Text Available A fireworks algorithm (FWA is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA. The purpose of this paper is to add opposition-based learning (OBL to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based adaptive fireworks algorithm (OAFWA. The final results conclude that OAFWA significantly outperformed EFWA and AFWA in terms of solution accuracy. Additionally, OAFWA was compared with a bat algorithm (BA, differential evolution (DE, self-adapting control parameters in differential evolution (jDE, a firefly algorithm (FA, and a standard particle swarm optimization 2011 (SPSO2011 algorithm. The research results indicate that OAFWA ranks the highest of the six algorithms for both solution accuracy and runtime cost.

Opposite Degree Algorithm and Its Applications

Directory of Open Access Journals (Sweden)

Xiao-Guang Yue

2015-12-01

Full Text Available The opposite (Opposite Degree, referred to as OD algorithm is an intelligent algorithm proposed by Yue Xiaoguang et al. Opposite degree algorithm is mainly based on the concept of opposite degree, combined with the idea of design of neural network and genetic algorithm and clustering analysis algorithm. The OD algorithm is divided into two sub algorithms, namely: opposite degree - numerical computation (OD-NC algorithm and opposite degree - Classification computation (OD-CC algorithm.

Algorithmic phase diagrams

Science.gov (United States)

Hockney, Roger

1987-01-01

Algorithmic phase diagrams are a neat and compact representation of the results of comparing the execution time of several algorithms for the solution of the same problem. As an example, the recent results are shown of Gannon and Van Rosendale on the solution of multiple tridiagonal systems of equations in the form of such diagrams. The act of preparing these diagrams has revealed an unexpectedly complex relationship between the best algorithm and the number and size of the tridiagonal systems, which was not evident from the algebraic formulae in the original paper. Even so, for a particular computer, one diagram suffices to predict the best algorithm for all problems that are likely to be encountered the prediction being read directly from the diagram without complex calculation.

Recursive forgetting algorithms

DEFF Research Database (Denmark)

Parkum, Jens; Poulsen, Niels Kjølstad; Holst, Jan

1992-01-01

In the first part of the paper, a general forgetting algorithm is formulated and analysed. It contains most existing forgetting schemes as special cases. Conditions are given ensuring that the basic convergence properties will hold. In the second part of the paper, the results are applied...... to a specific algorithm with selective forgetting. Here, the forgetting is non-uniform in time and space. The theoretical analysis is supported by a simulation example demonstrating the practical performance of this algorithm...

Discrete computational mechanics for stiff phenomena

KAUST Repository

Michels, Dominik L.

2016-11-28

Many natural phenomena which occur in the realm of visual computing and computational physics, like the dynamics of cloth, fibers, fluids, and solids as well as collision scenarios are described by stiff Hamiltonian equations of motion, i.e. differential equations whose solution spectra simultaneously contain extremely high and low frequencies. This usually impedes the development of physically accurate and at the same time efficient integration algorithms. We present a straightforward computationally oriented introduction to advanced concepts from classical mechanics. We provide an easy to understand step-by-step introduction from variational principles over the Euler-Lagrange formalism and the Legendre transformation to Hamiltonian mechanics. Based on such solid theoretical foundations, we study the underlying geometric structure of Hamiltonian systems as well as their discrete counterparts in order to develop sophisticated structure preserving integration algorithms to efficiently perform high fidelity simulations.

Global track finder for Belle II experiment

Energy Technology Data Exchange (ETDEWEB)

Trusov, Viktor; Feindt, Michael; Heck, Martin; Kuhr, Thomas; Goldenzweig, Pablo [Karlsruhe Institute of Technology, IEKP (Germany); Collaboration: Belle II-Collaboration

2015-07-01

We present an implementation of a method based on the Legendre transformation for reconstruction charged particle tracks in the central drift chamber of the Belle II experiment. The method is designed for fast track finding and restoring circular patterns of track hits in transverse plane. It is done by searching for common tangents to drift circles of hits in the conformal space. With known transverse trajectories longitudinal momentum estimation performed by assigning stereo hits followed by determination of the track parameters. The method includes algorithms responsible for track quality estimation and reduction of rate of fakes. The work is targeting at increasing the efficiency and reducing the execution time because the computing power available to the experiment is limited. The algorithm is developed within the Belle II software environment with using Monte-Carlo simulation for probing its efficiency.

Agency and Algorithms

Directory of Open Access Journals (Sweden)

Hanns Holger Rutz

2016-11-01

Full Text Available Although the concept of algorithms has been established a long time ago, their current topicality indicates a shift in the discourse. Classical definitions based on logic seem to be inadequate to describe their aesthetic capabilities. New approaches stress their involvement in material practices as well as their incompleteness. Algorithmic aesthetics can no longer be tied to the static analysis of programs, but must take into account the dynamic and experimental nature of coding practices. It is suggested that the aesthetic objects thus produced articulate something that could be called algorithmicity or the space of algorithmic agency. This is the space or the medium – following Luhmann’s form/medium distinction – where human and machine undergo mutual incursions. In the resulting coupled “extimate” writing process, human initiative and algorithmic speculation cannot be clearly divided out any longer. An observation is attempted of defining aspects of such a medium by drawing a trajectory across a number of sound pieces. The operation of exchange between form and medium I call reconfiguration and it is indicated by this trajectory. 

Real-Coded Quantum-Inspired Genetic Algorithm-Based BP Neural Network Algorithm

Directory of Open Access Journals (Sweden)

Jianyong Liu

2015-01-01

Full Text Available The method that the real-coded quantum-inspired genetic algorithm (RQGA used to optimize the weights and threshold of BP neural network is proposed to overcome the defect that the gradient descent method makes the algorithm easily fall into local optimal value in the learning process. Quantum genetic algorithm (QGA is with good directional global optimization ability, but the conventional QGA is based on binary coding; the speed of calculation is reduced by the coding and decoding processes. So, RQGA is introduced to explore the search space, and the improved varied learning rate is adopted to train the BP neural network. Simulation test shows that the proposed algorithm is effective to rapidly converge to the solution conformed to constraint conditions.

A cluster algorithm for graphs

NARCIS (Netherlands)

S. van Dongen

2000-01-01

textabstractA cluster algorithm for graphs called the emph{Markov Cluster algorithm (MCL~algorithm) is introduced. The algorithm provides basically an interface to an algebraic process defined on stochastic matrices, called the MCL~process. The graphs may be both weighted (with nonnegative weight)

Unsupervised learning algorithms

CERN Document Server

Aydin, Kemal

2016-01-01

This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering,...

Generalized-ensemble molecular dynamics and Monte Carlo algorithms beyond the limit of the multicanonical algorithm

International Nuclear Information System (INIS)

Okumura, Hisashi

2010-01-01

I review two new generalized-ensemble algorithms for molecular dynamics and Monte Carlo simulations of biomolecules, that is, the multibaric–multithermal algorithm and the partial multicanonical algorithm. In the multibaric–multithermal algorithm, two-dimensional random walks not only in the potential-energy space but also in the volume space are realized. One can discuss the temperature dependence and pressure dependence of biomolecules with this algorithm. The partial multicanonical simulation samples a wide range of only an important part of potential energy, so that one can concentrate the effort to determine a multicanonical weight factor only on the important energy terms. This algorithm has higher sampling efficiency than the multicanonical and canonical algorithms. (review)

Theoretic derivation of directed acyclic subgraph algorithm and comparisons with message passing algorithm

Science.gov (United States)

Ha, Jeongmok; Jeong, Hong

2016-07-01

This study investigates the directed acyclic subgraph (DAS) algorithm, which is used to solve discrete labeling problems much more rapidly than other Markov-random-field-based inference methods but at a competitive accuracy. However, the mechanism by which the DAS algorithm simultaneously achieves competitive accuracy and fast execution speed, has not been elucidated by a theoretical derivation. We analyze the DAS algorithm by comparing it with a message passing algorithm. Graphical models, inference methods, and energy-minimization frameworks are compared between DAS and message passing algorithms. Moreover, the performances of DAS and other message passing methods [sum-product belief propagation (BP), max-product BP, and tree-reweighted message passing] are experimentally compared.

Shadow algorithms data miner

CERN Document Server

Woo, Andrew

2012-01-01

Digital shadow generation continues to be an important aspect of visualization and visual effects in film, games, simulations, and scientific applications. This resource offers a thorough picture of the motivations, complexities, and categorized algorithms available to generate digital shadows. From general fundamentals to specific applications, it addresses shadow algorithms and how to manage huge data sets from a shadow perspective. The book also examines the use of shadow algorithms in industrial applications, in terms of what algorithms are used and what software is applicable.

Diversity-Guided Evolutionary Algorithms

DEFF Research Database (Denmark)

Ursem, Rasmus Kjær

2002-01-01

Population diversity is undoubtably a key issue in the performance of evolutionary algorithms. A common hypothesis is that high diversity is important to avoid premature convergence and to escape local optima. Various diversity measures have been used to analyze algorithms, but so far few...... algorithms have used a measure to guide the search. The diversity-guided evolutionary algorithm (DGEA) uses the wellknown distance-to-average-point measure to alternate between phases of exploration (mutation) and phases of exploitation (recombination and selection). The DGEA showed remarkable results...

Contact-impact algorithms on parallel computers

International Nuclear Information System (INIS)

Zhong Zhihua; Nilsson, Larsgunnar

1994-01-01

Contact-impact algorithms on parallel computers are discussed within the context of explicit finite element analysis. The algorithms concerned include a contact searching algorithm and an algorithm for contact force calculations. The contact searching algorithm is based on the territory concept of the general HITA algorithm. However, no distinction is made between different contact bodies, or between different contact surfaces. All contact segments from contact boundaries are taken as a single set. Hierarchy territories and contact territories are expanded. A three-dimensional bucket sort algorithm is used to sort contact nodes. The defence node algorithm is used in the calculation of contact forces. Both the contact searching algorithm and the defence node algorithm are implemented on the connection machine CM-200. The performance of the algorithms is examined under different circumstances, and numerical results are presented. ((orig.))

A review on quantum search algorithms

Science.gov (United States)

Giri, Pulak Ranjan; Korepin, Vladimir E.

2017-12-01

The use of superposition of states in quantum computation, known as quantum parallelism, has significant advantage in terms of speed over the classical computation. It is evident from the early invented quantum algorithms such as Deutsch's algorithm, Deutsch-Jozsa algorithm and its variation as Bernstein-Vazirani algorithm, Simon algorithm, Shor's algorithms, etc. Quantum parallelism also significantly speeds up the database search algorithm, which is important in computer science because it comes as a subroutine in many important algorithms. Quantum database search of Grover achieves the task of finding the target element in an unsorted database in a time quadratically faster than the classical computer. We review Grover's quantum search algorithms for a singe and multiple target elements in a database. The partial search algorithm of Grover and Radhakrishnan and its optimization by Korepin called GRK algorithm are also discussed.

Magnet sorting algorithms

International Nuclear Information System (INIS)

Dinev, D.

1996-01-01

Several new algorithms for sorting of dipole and/or quadrupole magnets in synchrotrons and storage rings are described. The algorithms make use of a combinatorial approach to the problem and belong to the class of random search algorithms. They use an appropriate metrization of the state space. The phase-space distortion (smear) is used as a goal function. Computational experiments for the case of the JINR-Dubna superconducting heavy ion synchrotron NUCLOTRON have shown a significant reduction of the phase-space distortion after the magnet sorting. (orig.)

A framework for simulating ultrasound imaging based on first order nonlinear pressure–velocity relations

DEFF Research Database (Denmark)

Du, Yigang; Fan, Rui; Li, Yong

2016-01-01

An ultrasound imaging framework modeled with the first order nonlinear pressure–velocity relations (NPVR) based simulation and implemented by a half-time staggered solution and pseudospectral method is presented in this paper. The framework is capable of simulating linear and nonlinear ultrasound...... propagation and reflections in a heterogeneous medium with different sound speeds and densities. It can be initialized with arbitrary focus, excitation and apodization for multiple individual channels in both 2D and 3D spatial fields. The simulated channel data can be generated using this framework......, and ultrasound image can be obtained by beamforming the simulated channel data. Various results simulated by different algorithms are illustrated for comparisons. The root mean square (RMS) errors for each compared pulses are calculated. The linear propagation is validated by an angular spectrum approach (ASA...

Composite Differential Search Algorithm

Directory of Open Access Journals (Sweden)

Bo Liu

2014-01-01

Full Text Available Differential search algorithm (DS is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.

Artifact removal algorithms for stroke detection using a multistatic MIST beamforming algorithm.

Science.gov (United States)

Ricci, E; Di Domenico, S; Cianca, E; Rossi, T

2015-01-01

Microwave imaging (MWI) has been recently proved as a promising imaging modality for low-complexity, low-cost and fast brain imaging tools, which could play a fundamental role to efficiently manage emergencies related to stroke and hemorrhages. This paper focuses on the UWB radar imaging approach and in particular on the processing algorithms of the backscattered signals. Assuming the use of the multistatic version of the MIST (Microwave Imaging Space-Time) beamforming algorithm, developed by Hagness et al. for the early detection of breast cancer, the paper proposes and compares two artifact removal algorithms. Artifacts removal is an essential step of any UWB radar imaging system and currently considered artifact removal algorithms have been shown not to be effective in the specific scenario of brain imaging. First of all, the paper proposes modifications of a known artifact removal algorithm. These modifications are shown to be effective to achieve good localization accuracy and lower false positives. However, the main contribution is the proposal of an artifact removal algorithm based on statistical methods, which allows to achieve even better performance but with much lower computational complexity.

Law and Order in Algorithmics

NARCIS (Netherlands)

Fokkinga, M.M.

1992-01-01

An algorithm is the input-output effect of a computer program; mathematically, the notion of algorithm comes close to the notion of function. Just as arithmetic is the theory and practice of calculating with numbers, so is ALGORITHMICS the theory and practice of calculating with algorithms. Just as

Algorithms in Algebraic Geometry

CERN Document Server

Dickenstein, Alicia; Sommese, Andrew J

2008-01-01

In the last decade, there has been a burgeoning of activity in the design and implementation of algorithms for algebraic geometric computation. Some of these algorithms were originally designed for abstract algebraic geometry, but now are of interest for use in applications and some of these algorithms were originally designed for applications, but now are of interest for use in abstract algebraic geometry. The workshop on Algorithms in Algebraic Geometry that was held in the framework of the IMA Annual Program Year in Applications of Algebraic Geometry by the Institute for Mathematics and Its

Explaining algorithms using metaphors

CERN Document Server

Forišek, Michal

2013-01-01

There is a significant difference between designing a new algorithm, proving its correctness, and teaching it to an audience. When teaching algorithms, the teacher's main goal should be to convey the underlying ideas and to help the students form correct mental models related to the algorithm. This process can often be facilitated by using suitable metaphors. This work provides a set of novel metaphors identified and developed as suitable tools for teaching many of the 'classic textbook' algorithms taught in undergraduate courses worldwide. Each chapter provides exercises and didactic notes fo

Portfolios of quantum algorithms.

Science.gov (United States)

Maurer, S M; Hogg, T; Huberman, B A

2001-12-17

Quantum computation holds promise for the solution of many intractable problems. However, since many quantum algorithms are stochastic in nature they can find the solution of hard problems only probabilistically. Thus the efficiency of the algorithms has to be characterized by both the expected time to completion and the associated variance. In order to minimize both the running time and its uncertainty, we show that portfolios of quantum algorithms analogous to those of finance can outperform single algorithms when applied to the NP-complete problems such as 3-satisfiability.

DNABIT Compress - Genome compression algorithm.

Science.gov (United States)

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-22

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that "DNABIT Compress" algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases.

Can we use the known fast spherical fourier transforms in numerical meterology?

OpenAIRE

Sprengel, F.

2001-01-01

In numerical meteorology, there are many solvers using spectral methods. Most of the computing time is spent computing the discrete Legendre function transforms. The aim of this paper is to clarify whether the recently published fast Legendre function transforms can be used here.

A verified LLL algorithm

NARCIS (Netherlands)

Divasón, Jose; Joosten, Sebastiaan; Thiemann, René; Yamada, Akihisa

2018-01-01

The Lenstra-Lenstra-Lovász basis reduction algorithm, also known as LLL algorithm, is an algorithm to find a basis with short, nearly orthogonal vectors of an integer lattice. Thereby, it can also be seen as an approximation to solve the shortest vector problem (SVP), which is an NP-hard problem,

SPECIAL LIBRARIES OF FRAGMENTS OF ALGORITHMIC NETWORKS TO AUTOMATE THE DEVELOPMENT OF ALGORITHMIC MODELS

Directory of Open Access Journals (Sweden)

V. E. Marley

2015-01-01

Full Text Available Summary. The concept of algorithmic models appeared from the algorithmic approach in which the simulated object, the phenomenon appears in the form of process, subject to strict rules of the algorithm, which placed the process of operation of the facility. Under the algorithmic model is the formalized description of the scenario subject specialist for the simulated process, the structure of which is comparable with the structure of the causal and temporal relationships between events of the process being modeled, together with all information necessary for its software implementation. To represent the structure of algorithmic models used algorithmic network. Normally, they were defined as loaded finite directed graph, the vertices which are mapped to operators and arcs are variables, bound by operators. The language of algorithmic networks has great features, the algorithms that it can display indifference the class of all random algorithms. In existing systems, automation modeling based on algorithmic nets, mainly used by operators working with real numbers. Although this reduces their ability, but enough for modeling a wide class of problems related to economy, environment, transport, technical processes. The task of modeling the execution of schedules and network diagrams is relevant and useful. There are many counting systems, network graphs, however, the monitoring process based analysis of gaps and terms of graphs, no analysis of prediction execution schedule or schedules. The library is designed to build similar predictive models. Specifying source data to obtain a set of projections from which to choose one and take it for a new plan.

Group leaders optimization algorithm

Science.gov (United States)

Daskin, Anmer; Kais, Sabre

2011-03-01

We present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique which is designed into a group architecture. To demonstrate the efficiency of the method, a standard suite of single and multi-dimensional optimization functions along with the energies and the geometric structures of Lennard-Jones clusters are given as well as the application of the algorithm on quantum circuit design problems. We show that as an improvement over previous methods, the algorithm scales as N 2.5 for the Lennard-Jones clusters of N-particles. In addition, an efficient circuit design is shown for a two-qubit Grover search algorithm which is a quantum algorithm providing quadratic speedup over the classical counterpart.

Totally parallel multilevel algorithms

Science.gov (United States)

Frederickson, Paul O.

1988-01-01

Four totally parallel algorithms for the solution of a sparse linear system have common characteristics which become quite apparent when they are implemented on a highly parallel hypercube such as the CM2. These four algorithms are Parallel Superconvergent Multigrid (PSMG) of Frederickson and McBryan, Robust Multigrid (RMG) of Hackbusch, the FFT based Spectral Algorithm, and Parallel Cyclic Reduction. In fact, all four can be formulated as particular cases of the same totally parallel multilevel algorithm, which are referred to as TPMA. In certain cases the spectral radius of TPMA is zero, and it is recognized to be a direct algorithm. In many other cases the spectral radius, although not zero, is small enough that a single iteration per timestep keeps the local error within the required tolerance.

Balancing Power Absorption and Structural Loading for a Novel Fixed-Bottom Wave Energy Converter with Nonideal Power Take-Off in Regular Waves: Preprint

Energy Technology Data Exchange (ETDEWEB)

Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yu, Yi-Hsiang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wright, Alan D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-06-08

In this work, the net power delivered to the grid from a nonideal power take-off (PTO) is introduced followed by a review of the pseudo-spectral control theory. A power-to-load ratio, used to evaluate the pseudo-spectral controller performance, is discussed, and the results obtained from optimizing a multiterm objective function are compared against results obtained from maximizing the net output power to the grid. Simulation results are then presented for four different oscillating wave energy converter geometries to highlight the potential of combing both geometry and PTO control to maximize power while minimizing loads.

The global Minmax k-means algorithm.

Science.gov (United States)

Wang, Xiaoyan; Bai, Yanping

2016-01-01

The global k -means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k -means to minimize the sum of the intra-cluster variances. However the global k -means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k -means algorithm. In this paper, we modified the global k -means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k -means clustering error method to global k -means algorithm to overcome the effect of bad initialization, proposed the global Minmax k -means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k -means algorithm, the global k -means algorithm and the MinMax k -means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.

New Optimization Algorithms in Physics

CERN Document Server

Hartmann, Alexander K

2004-01-01

Many physicists are not aware of the fact that they can solve their problems by applying optimization algorithms. Since the number of such algorithms is steadily increasing, many new algorithms have not been presented comprehensively until now. This presentation of recently developed algorithms applied in physics, including demonstrations of how they work and related results, aims to encourage their application, and as such the algorithms selected cover concepts and methods from statistical physics to optimization problems emerging in theoretical computer science.

Learning algorithms and automatic processing of languages; Algorithmes a apprentissage et traitement automatique des langues

Energy Technology Data Exchange (ETDEWEB)

Fluhr, Christian Yves Andre

1977-06-15

This research thesis concerns the field of artificial intelligence. It addresses learning algorithms applied to automatic processing of languages. The author first briefly describes some mechanisms of human intelligence in order to describe how these mechanisms are simulated on a computer. He outlines the specific role of learning in various manifestations of intelligence. Then, based on the Markov's algorithm theory, the author discusses the notion of learning algorithm. Two main types of learning algorithms are then addressed: firstly, an 'algorithm-teacher dialogue' type sanction-based algorithm which aims at learning how to solve grammatical ambiguities in submitted texts; secondly, an algorithm related to a document system which structures semantic data automatically obtained from a set of texts in order to be able to understand by references to any question on the content of these texts.

Graph Colouring Algorithms

DEFF Research Database (Denmark)

Husfeldt, Thore

2015-01-01

This chapter presents an introduction to graph colouring algorithms. The focus is on vertex-colouring algorithms that work for general classes of graphs with worst-case performance guarantees in a sequential model of computation. The presentation aims to demonstrate the breadth of available...

FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

Directory of Open Access Journals (Sweden)

G. Sithole

2015-05-01

Full Text Available The notion of a ‘Best’ segmentation does not exist. A segmentation algorithm is chosen based on the features it yields, the properties of the segments (point sets it generates, and the complexity of its algorithm. The segmentation is then assessed based on a variety of metrics such as homogeneity, heterogeneity, fragmentation, etc. Even after an algorithm is chosen its performance is still uncertain because the landscape/scenarios represented in a point cloud have a strong influence on the eventual segmentation. Thus selecting an appropriate segmentation algorithm is a process of trial and error. Automating the selection of segmentation algorithms and their parameters first requires methods to evaluate segmentations. Three common approaches for evaluating segmentation algorithms are ‘goodness methods’, ‘discrepancy methods’ and ‘benchmarks’. Benchmarks are considered the most comprehensive method of evaluation. This paper shortcomings in current benchmark methods are identified and a framework is proposed that permits both a visual and numerical evaluation of segmentations for different algorithms, algorithm parameters and evaluation metrics. The concept of the framework is demonstrated on a real point cloud. Current results are promising and suggest that it can be used to predict the performance of segmentation algorithms.

From Genetics to Genetic Algorithms

Indian Academy of Sciences (India)

Genetic algorithms (GAs) are computational optimisation schemes with an ... The algorithms solve optimisation problems ..... Genetic Algorithms in Search, Optimisation and Machine. Learning, Addison-Wesley Publishing Company, Inc. 1989.

Quantum random-walk search algorithm

International Nuclear Information System (INIS)

Shenvi, Neil; Whaley, K. Birgitta; Kempe, Julia

2003-01-01

Quantum random walks on graphs have been shown to display many interesting properties, including exponentially fast hitting times when compared with their classical counterparts. However, it is still unclear how to use these novel properties to gain an algorithmic speedup over classical algorithms. In this paper, we present a quantum search algorithm based on the quantum random-walk architecture that provides such a speedup. It will be shown that this algorithm performs an oracle search on a database of N items with O(√(N)) calls to the oracle, yielding a speedup similar to other quantum search algorithms. It appears that the quantum random-walk formulation has considerable flexibility, presenting interesting opportunities for development of other, possibly novel quantum algorithms

Recognition algorithms in knot theory

International Nuclear Information System (INIS)

Dynnikov, I A

2003-01-01

In this paper the problem of constructing algorithms for comparing knots and links is discussed. A survey of existing approaches and basic results in this area is given. In particular, diverse combinatorial methods for representing links are discussed, the Haken algorithm for recognizing a trivial knot (the unknot) and a scheme for constructing a general algorithm (using Haken's ideas) for comparing links are presented, an approach based on representing links by closed braids is described, the known algorithms for solving the word problem and the conjugacy problem for braid groups are described, and the complexity of the algorithms under consideration is discussed. A new method of combinatorial description of knots is given together with a new algorithm (based on this description) for recognizing the unknot by using a procedure for monotone simplification. In the conclusion of the paper several problems are formulated whose solution could help to advance towards the 'algorithmization' of knot theory

Fast algorithm for Morphological Filters

International Nuclear Information System (INIS)

Lou Shan; Jiang Xiangqian; Scott, Paul J

2011-01-01

In surface metrology, morphological filters, which evolved from the envelope filtering system (E-system) work well for functional prediction of surface finish in the analysis of surfaces in contact. The naive algorithms are time consuming, especially for areal data, and not generally adopted in real practice. A fast algorithm is proposed based on the alpha shape. The hull obtained by rolling the alpha ball is equivalent to the morphological opening/closing in theory. The algorithm depends on Delaunay triangulation with time complexity O(nlogn). In comparison to the naive algorithms it generates the opening and closing envelope without combining dilation and erosion. Edge distortion is corrected by reflective padding for open profiles/surfaces. Spikes in the sample data are detected and points interpolated to prevent singularities. The proposed algorithm works well both for morphological profile and area filters. Examples are presented to demonstrate the validity and superiority on efficiency of this algorithm over the naive algorithm.

An Algorithm Computing the Local $b$ Function by an Approximate Division Algorithm in $\\hat{\\mathcal{D}}$

OpenAIRE

Nakayama, Hiromasa

2006-01-01

We give an algorithm to compute the local $b$ function. In this algorithm, we use the Mora division algorithm in the ring of differential operators and an approximate division algorithm in the ring of differential operators with power series coefficient.

Introduction to Evolutionary Algorithms

CERN Document Server

Yu, Xinjie

2010-01-01

Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization, particle swarm opti

Evidence-based algorithm for heparin dosing before cardiopulmonary bypass. Part 1: Development of the algorithm.

Science.gov (United States)

McKinney, Mark C; Riley, Jeffrey B

2007-12-01

The incidence of heparin resistance during adult cardiac surgery with cardiopulmonary bypass has been reported at 15%-20%. The consistent use of a clinical decision-making algorithm may increase the consistency of patient care and likely reduce the total required heparin dose and other problems associated with heparin dosing. After a directed survey of practicing perfusionists regarding treatment of heparin resistance and a literature search for high-level evidence regarding the diagnosis and treatment of heparin resistance, an evidence-based decision-making algorithm was constructed. The face validity of the algorithm decisive steps and logic was confirmed by a second survey of practicing perfusionists. The algorithm begins with review of the patient history to identify predictors for heparin resistance. The definition for heparin resistance contained in the algorithm is an activated clotting time 450 IU/kg heparin loading dose. Based on the literature, the treatment for heparin resistance used in the algorithm is anti-thrombin III supplement. The algorithm seems to be valid and is supported by high-level evidence and clinician opinion. The next step is a human randomized clinical trial to test the clinical procedure guideline algorithm vs. current standard clinical practice.

Algorithmic Principles of Mathematical Programming

NARCIS (Netherlands)

Faigle, Ulrich; Kern, Walter; Still, Georg

2002-01-01

Algorithmic Principles of Mathematical Programming investigates the mathematical structures and principles underlying the design of efficient algorithms for optimization problems. Recent advances in algorithmic theory have shown that the traditionally separate areas of discrete optimization, linear

ADORE-GA: Genetic algorithm variant of the ADORE algorithm for ROP detector layout optimization in CANDU reactors

International Nuclear Information System (INIS)

Kastanya, Doddy

2012-01-01

Highlights: ► ADORE is an algorithm for CANDU ROP Detector Layout Optimization. ► ADORE-GA is a Genetic Algorithm variant of the ADORE algorithm. ► Robustness test of ADORE-GA algorithm is presented in this paper. - Abstract: The regional overpower protection (ROP) systems protect CANDU® reactors against overpower in the fuel that could reduce the safety margin-to-dryout. The overpower could originate from a localized power peaking within the core or a general increase in the global core power level. The design of the detector layout for ROP systems is a challenging discrete optimization problem. In recent years, two algorithms have been developed to find a quasi optimal solution to this detector layout optimization problem. Both of these algorithms utilize the simulated annealing (SA) algorithm as their optimization engine. In the present paper, an alternative optimization algorithm, namely the genetic algorithm (GA), has been implemented as the optimization engine. The implementation is done within the ADORE algorithm. Results from evaluating the effects of using various mutation rates and crossover parameters are presented in this paper. It has been demonstrated that the algorithm is sufficiently robust in producing similar quality solutions.

Where genetic algorithms excel.

Science.gov (United States)

Baum, E B; Boneh, D; Garrett, C

2001-01-01

We analyze the performance of a genetic algorithm (GA) we call Culling, and a variety of other algorithms, on a problem we refer to as the Additive Search Problem (ASP). We show that the problem of learning the Ising perceptron is reducible to a noisy version of ASP. Noisy ASP is the first problem we are aware of where a genetic-type algorithm bests all known competitors. We generalize ASP to k-ASP to study whether GAs will achieve "implicit parallelism" in a problem with many more schemata. GAs fail to achieve this implicit parallelism, but we describe an algorithm we call Explicitly Parallel Search that succeeds. We also compute the optimal culling point for selective breeding, which turns out to be independent of the fitness function or the population distribution. We also analyze a mean field theoretic algorithm performing similarly to Culling on many problems. These results provide insight into when and how GAs can beat competing methods.

Mao-Gilles Stabilization Algorithm

OpenAIRE

Jérôme Gilles

2013-01-01

Originally, the Mao-Gilles stabilization algorithm was designed to compensate the non-rigid deformations due to atmospheric turbulence. Given a sequence of frames affected by atmospheric turbulence, the algorithm uses a variational model combining optical flow and regularization to characterize the static observed scene. The optimization problem is solved by Bregman Iteration and the operator splitting method. The algorithm is simple, efficient, and can be easily generalized for different sce...

Efficient GPS Position Determination Algorithms

National Research Council Canada - National Science Library

Nguyen, Thao Q

2007-01-01

... differential GPS algorithm for a network of users. The stand-alone user GPS algorithm is a direct, closed-form, and efficient new position determination algorithm that exploits the closed-form solution of the GPS trilateration equations and works...

Improved autonomous star identification algorithm

International Nuclear Information System (INIS)

Luo Li-Yan; Xu Lu-Ping; Zhang Hua; Sun Jing-Rong

2015-01-01

The log–polar transform (LPT) is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm. (paper)

Fluid-structure-coupling algorithm

International Nuclear Information System (INIS)

McMaster, W.H.; Gong, E.Y.; Landram, C.S.; Quinones, D.F.

1980-01-01

A fluid-structure-interaction algorithm has been developed and incorporated into the two dimensional code PELE-IC. This code combines an Eulerian incompressible fluid algorithm with a Lagrangian finite element shell algorithm and incorporates the treatment of complex free surfaces. The fluid structure, and coupling algorithms have been verified by the calculation of solved problems from the literature and from air and steam blowdown experiments. The code has been used to calculate loads and structural response from air blowdown and the oscillatory condensation of steam bubbles in water suppression pools typical of boiling water reactors. The techniques developed here have been extended to three dimensions and implemented in the computer code PELE-3D

Fluid structure coupling algorithm

International Nuclear Information System (INIS)

McMaster, W.H.; Gong, E.Y.; Landram, C.S.; Quinones, D.F.

1980-01-01

A fluid-structure-interaction algorithm has been developed and incorporated into the two-dimensional code PELE-IC. This code combines an Eulerian incompressible fluid algorithm with a Lagrangian finite element shell algorithm and incorporates the treatment of complex free surfaces. The fluid structure and coupling algorithms have been verified by the calculation of solved problems from the literature and from air and steam blowdown experiments. The code has been used to calculate loads and structural response from air blowdown and the oscillatory condensation of steam bubbles in water suppression pools typical of boiling water reactors. The techniques developed have been extended to three dimensions and implemented in the computer code PELE-3D

Majorization arrow in quantum-algorithm design

International Nuclear Information System (INIS)

Latorre, J.I.; Martin-Delgado, M.A.

2002-01-01

We apply majorization theory to study the quantum algorithms known so far and find that there is a majorization principle underlying the way they operate. Grover's algorithm is a neat instance of this principle where majorization works step by step until the optimal target state is found. Extensions of this situation are also found in algorithms based in quantum adiabatic evolution and the family of quantum phase-estimation algorithms, including Shor's algorithm. We state that in quantum algorithms the time arrow is a majorization arrow

Foundations of genetic algorithms 1991

CERN Document Server

1991-01-01

Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems.This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination, parallelization, and population divergence. Other topics include the non-uniform Walsh-schema transform; spurious correlations and premature convergence in genetic algorithms; and variable default hierarchy separation in a classifier system. The grammar-based genetic algorithm; condition

Opposition-Based Adaptive Fireworks Algorithm

OpenAIRE

Chibing Gong

2016-01-01

A fireworks algorithm (FWA) is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA) proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA). The purpose of this paper is to add opposition-based learning (OBL) to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based a...

Chinese handwriting recognition an algorithmic perspective

CERN Document Server

Su, Tonghua

2013-01-01

This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping ...

Combinatorial algorithms

CERN Document Server

Hu, T C

2002-01-01

Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9

THE APPROACHING TRAIN DETECTION ALGORITHM

OpenAIRE

S. V. Bibikov

2015-01-01

The paper deals with detection algorithm for rail vibroacoustic waves caused by approaching train on the background of increased noise. The urgency of algorithm development for train detection in view of increased rail noise, when railway lines are close to roads or road intersections is justified. The algorithm is based on the method of weak signals detection in a noisy environment. The information statistics ultimate expression is adjusted. We present the results of algorithm research and t...

Combinatorial optimization algorithms and complexity

CERN Document Server

Papadimitriou, Christos H

1998-01-01

This clearly written, mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. All chapters are supplemented by thought-provoking problems. A useful work for graduate-level students with backgrounds in computer science, operations research, and electrical engineering.

Enhanced sampling algorithms.

Science.gov (United States)

Mitsutake, Ayori; Mori, Yoshiharu; Okamoto, Yuko

2013-01-01

In biomolecular systems (especially all-atom models) with many degrees of freedom such as proteins and nucleic acids, there exist an astronomically large number of local-minimum-energy states. Conventional simulations in the canonical ensemble are of little use, because they tend to get trapped in states of these energy local minima. Enhanced conformational sampling techniques are thus in great demand. A simulation in generalized ensemble performs a random walk in potential energy space and can overcome this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review uses of the generalized-ensemble algorithms in biomolecular systems. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present various extensions of these three generalized-ensemble algorithms. The effectiveness of the methods is tested with short peptide and protein systems.

Economic dispatch using chaotic bat algorithm

International Nuclear Information System (INIS)

Adarsh, B.R.; Raghunathan, T.; Jayabarathi, T.; Yang, Xin-She

2016-01-01

This paper presents the application of a new metaheuristic optimization algorithm, the chaotic bat algorithm for solving the economic dispatch problem involving a number of equality and inequality constraints such as power balance, prohibited operating zones and ramp rate limits. Transmission losses and multiple fuel options are also considered for some problems. The chaotic bat algorithm, a variant of the basic bat algorithm, is obtained by incorporating chaotic sequences to enhance its performance. Five different example problems comprising 6, 13, 20, 40 and 160 generating units are solved to demonstrate the effectiveness of the algorithm. The algorithm requires little tuning by the user, and the results obtained show that it either outperforms or compares favorably with several existing techniques reported in literature. - Highlights: • The chaotic bat algorithm, a new metaheuristic optimization algorithm has been used. • The problem solved – the economic dispatch problem – is nonlinear, discontinuous. • It has number of equality and inequality constraints. • The algorithm has been demonstrated to be applicable on high dimensional problems.

Inclusive Flavour Tagging Algorithm

International Nuclear Information System (INIS)

Likhomanenko, Tatiana; Derkach, Denis; Rogozhnikov, Alex

2016-01-01

Identifying the flavour of neutral B mesons production is one of the most important components needed in the study of time-dependent CP violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm as an upgrade of the algorithms currently used by the LHCb experiment. Specifically, a probabilistic model which efficiently combines information from reconstructed vertices and tracks using machine learning is proposed. The algorithm does not use information about underlying physics process. It reduces the dependence on the performance of lower level identification capacities and thus increases the overall performance. The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of B mesons in any proton-proton experiment. (paper)

Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

Science.gov (United States)

Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

2016-03-03

This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

Multistage Spectral Relaxation Method for Solving the Hyperchaotic Complex Systems

Directory of Open Access Journals (Sweden)

Hassan Saberi Nik

2014-01-01

Full Text Available We present a pseudospectral method application for solving the hyperchaotic complex systems. The proposed method, called the multistage spectral relaxation method (MSRM is based on a technique of extending Gauss-Seidel type relaxation ideas to systems of nonlinear differential equations and using the Chebyshev pseudospectral methods to solve the resulting system on a sequence of multiple intervals. In this new application, the MSRM is used to solve famous hyperchaotic complex systems such as hyperchaotic complex Lorenz system and the complex permanent magnet synchronous motor. We compare this approach to the Runge-Kutta based ode45 solver to show that the MSRM gives accurate results.

A survey of parallel multigrid algorithms

Science.gov (United States)

Chan, Tony F.; Tuminaro, Ray S.

1987-01-01

A typical multigrid algorithm applied to well-behaved linear-elliptic partial-differential equations (PDEs) is described. Criteria for designing and evaluating parallel algorithms are presented. Before evaluating the performance of some parallel multigrid algorithms, consideration is given to some theoretical complexity results for solving PDEs in parallel and for executing the multigrid algorithm. The effect of mapping and load imbalance on the partial efficiency of the algorithm is studied.

Autodriver algorithm

Directory of Open Access Journals (Sweden)

Anna Bourmistrova

2011-02-01

Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.

Quantum algorithm for support matrix machines

Science.gov (United States)

Duan, Bojia; Yuan, Jiabin; Liu, Ying; Li, Dan

2017-09-01

We propose a quantum algorithm for support matrix machines (SMMs) that efficiently addresses an image classification problem by introducing a least-squares reformulation. This algorithm consists of two core subroutines: a quantum matrix inversion (Harrow-Hassidim-Lloyd, HHL) algorithm and a quantum singular value thresholding (QSVT) algorithm. The two algorithms can be implemented on a universal quantum computer with complexity O[log(npq) ] and O[log(pq)], respectively, where n is the number of the training data and p q is the size of the feature space. By iterating the algorithms, we can find the parameters for the SMM classfication model. Our analysis shows that both HHL and QSVT algorithms achieve an exponential increase of speed over their classical counterparts.

Mao-Gilles Stabilization Algorithm

Directory of Open Access Journals (Sweden)

Jérôme Gilles

2013-07-01

Full Text Available Originally, the Mao-Gilles stabilization algorithm was designed to compensate the non-rigid deformations due to atmospheric turbulence. Given a sequence of frames affected by atmospheric turbulence, the algorithm uses a variational model combining optical flow and regularization to characterize the static observed scene. The optimization problem is solved by Bregman Iteration and the operator splitting method. The algorithm is simple, efficient, and can be easily generalized for different scenarios involving non-rigid deformations.

Effects of visualization on algorithm comprehension

Science.gov (United States)

Mulvey, Matthew

Computer science students are expected to learn and apply a variety of core algorithms which are an essential part of the field. Any one of these algorithms by itself is not necessarily extremely complex, but remembering the large variety of algorithms and the differences between them is challenging. To address this challenge, we present a novel algorithm visualization tool designed to enhance students understanding of Dijkstra's algorithm by allowing them to discover the rules of the algorithm for themselves. It is hoped that a deeper understanding of the algorithm will help students correctly select, adapt and apply the appropriate algorithm when presented with a problem to solve, and that what is learned here will be applicable to the design of other visualization tools designed to teach different algorithms. Our visualization tool is currently in the prototype stage, and this thesis will discuss the pedagogical approach that informs its design, as well as the results of some initial usability testing. Finally, to clarify the direction for further development of the tool, four different variations of the prototype were implemented, and the instructional effectiveness of each was assessed by having a small sample participants use the different versions of the prototype and then take a quiz to assess their comprehension of the algorithm.

Algorithmic approach to diagram techniques

International Nuclear Information System (INIS)

Ponticopoulos, L.

1980-10-01

An algorithmic approach to diagram techniques of elementary particles is proposed. The definition and axiomatics of the theory of algorithms are presented, followed by the list of instructions of an algorithm formalizing the construction of graphs and the assignment of mathematical objects to them. (T.A.)

Multisensor data fusion algorithm development

Energy Technology Data Exchange (ETDEWEB)

Yocky, D.A.; Chadwick, M.D.; Goudy, S.P.; Johnson, D.K.

1995-12-01

This report presents a two-year LDRD research effort into multisensor data fusion. We approached the problem by addressing the available types of data, preprocessing that data, and developing fusion algorithms using that data. The report reflects these three distinct areas. First, the possible data sets for fusion are identified. Second, automated registration techniques for imagery data are analyzed. Third, two fusion techniques are presented. The first fusion algorithm is based on the two-dimensional discrete wavelet transform. Using test images, the wavelet algorithm is compared against intensity modulation and intensity-hue-saturation image fusion algorithms that are available in commercial software. The wavelet approach outperforms the other two fusion techniques by preserving spectral/spatial information more precisely. The wavelet fusion algorithm was also applied to Landsat Thematic Mapper and SPOT panchromatic imagery data. The second algorithm is based on a linear-regression technique. We analyzed the technique using the same Landsat and SPOT data.

A new cluster algorithm for graphs

NARCIS (Netherlands)

S. van Dongen

1998-01-01

textabstractA new cluster algorithm for graphs called the emph{Markov Cluster algorithm ($MCL$ algorithm) is introduced. The graphs may be both weighted (with nonnegative weight) and directed. Let~$G$~be such a graph. The $MCL$ algorithm simulates flow in $G$ by first identifying $G$ in a

An overview of smart grid routing algorithms

Science.gov (United States)

Wang, Junsheng; OU, Qinghai; Shen, Haijuan

2017-08-01

This paper summarizes the typical routing algorithm in smart grid by analyzing the communication business and communication requirements of intelligent grid. Mainly from the two kinds of routing algorithm is analyzed, namely clustering routing algorithm and routing algorithm, analyzed the advantages and disadvantages of two kinds of typical routing algorithm in routing algorithm and applicability.

A Parametric k-Means Algorithm

Science.gov (United States)

Tarpey, Thaddeus

2007-01-01

Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

DNABIT Compress – Genome compression algorithm

Science.gov (United States)

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-01

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, “DNABIT Compress” for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that “DNABIT Compress” algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases. PMID:21383923

Some software algorithms for microprocessor ratemeters

International Nuclear Information System (INIS)

Savic, Z.

1991-01-01

After a review of the basic theoretical ratemeter problem and a general discussion of microprocessor ratemeters, a short insight into their hardware organization is given. Three software algorithms are described: the old ones the quasi-exponential and floating mean algorithm, and a new weighted moving average algorithm. The equations for statistical characterization of the new algorithm are given and an intercomparison is made. It is concluded that the new algorithm has statistical advantages over the old ones. (orig.)

Some software algorithms for microprocessor ratemeters

Energy Technology Data Exchange (ETDEWEB)

Savic, Z. (Military Technical Inst., Belgrade (Yugoslavia))

1991-03-15

After a review of the basic theoretical ratemeter problem and a general discussion of microprocessor ratemeters, a short insight into their hardware organization is given. Three software algorithms are described: the old ones the quasi-exponential and floating mean algorithm, and a new weighted moving average algorithm. The equations for statistical characterization of the new algorithm are given and an intercomparison is made. It is concluded that the new algorithm has statistical advantages over the old ones. (orig.).

Higher-order force gradient symplectic algorithms

Science.gov (United States)

Chin, Siu A.; Kidwell, Donald W.

2000-12-01

We show that a recently discovered fourth order symplectic algorithm, which requires one evaluation of force gradient in addition to three evaluations of the force, when iterated to higher order, yielded algorithms that are far superior to similarly iterated higher order algorithms based on the standard Forest-Ruth algorithm. We gauge the accuracy of each algorithm by comparing the step-size independent error functions associated with energy conservation and the rotation of the Laplace-Runge-Lenz vector when solving a highly eccentric Kepler problem. For orders 6, 8, 10, and 12, the new algorithms are approximately a factor of 103, 104, 104, and 105 better.

The Retina Algorithm

CERN Multimedia

CERN. Geneva; PUNZI, Giovanni

2015-01-01

Charge particle reconstruction is one of the most demanding computational tasks found in HEP, and it becomes increasingly important to perform it in real time. We envision that HEP would greatly benefit from achieving a long-term goal of making track reconstruction happen transparently as part of the detector readout ("detector-embedded tracking"). We describe here a track-reconstruction approach based on a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature ('RETINA algorithm'). It turns out that high-quality tracking in large HEP detectors is possible with very small latencies, when this algorithm is implemented in specialized processors, based on current state-of-the-art, high-speed/high-bandwidth digital devices.

Machine Learning an algorithmic perspective

CERN Document Server

Marsland, Stephen

2009-01-01

Traditional books on machine learning can be divided into two groups - those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement le

Instance-specific algorithm configuration

CERN Document Server

Malitsky, Yuri

2014-01-01

This book presents a modular and expandable technique in the rapidly emerging research area of automatic configuration and selection of the best algorithm for the instance at hand. The author presents the basic model behind ISAC and then details a number of modifications and practical applications. In particular, he addresses automated feature generation, offline algorithm configuration for portfolio generation, algorithm selection, adaptive solvers, online tuning, and parallelization.    The author's related thesis was honorably mentioned (runner-up) for the ACP Dissertation Award in 2014,

Quantum algorithm for linear regression

Science.gov (United States)

Wang, Guoming

2017-07-01

We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

Algorithm FIRE-Feynman Integral REduction

International Nuclear Information System (INIS)

Smirnov, A.V.

2008-01-01

The recently developed algorithm FIRE performs the reduction of Feynman integrals to master integrals. It is based on a number of strategies, such as applying the Laporta algorithm, the s-bases algorithm, region-bases and integrating explicitly over loop momenta when possible. Currently it is being used in complicated three-loop calculations.

Synthesis of Greedy Algorithms Using Dominance Relations

Science.gov (United States)

Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.

2010-01-01

Greedy algorithms exploit problem structure and constraints to achieve linear-time performance. Yet there is still no completely satisfactory way of constructing greedy algorithms. For example, the Greedy Algorithm of Edmonds depends upon translating a problem into an algebraic structure called a matroid, but the existence of such a translation can be as hard to determine as the existence of a greedy algorithm itself. An alternative characterization of greedy algorithms is in terms of dominance relations, a well-known algorithmic technique used to prune search spaces. We demonstrate a process by which dominance relations can be methodically derived for a number of greedy algorithms, including activity selection, and prefix-free codes. By incorporating our approach into an existing framework for algorithm synthesis, we demonstrate that it could be the basis for an effective engineering method for greedy algorithms. We also compare our approach with other characterizations of greedy algorithms.

Algorithm for Compressing Time-Series Data

Science.gov (United States)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Algorithms

Indian Academy of Sciences (India)

ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...

Novel medical image enhancement algorithms

Science.gov (United States)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Wavelet-LMS algorithm-based echo cancellers

Science.gov (United States)

Seetharaman, Lalith K.; Rao, Sathyanarayana S.

2002-12-01

This paper presents Echo Cancellers based on the Wavelet-LMS Algorithm. The performance of the Least Mean Square Algorithm in Wavelet transform domain is observed and its application in Echo cancellation is analyzed. The Widrow-Hoff Least Mean Square Algorithm is most widely used algorithm for Adaptive filters that function as Echo Cancellers. The present day communication signals are widely non-stationary in nature and some errors crop up when Least Mean Square Algorithm is used for the Echo Cancellers handling such signals. The analysis of non-stationary signals often involves a compromise between how well transitions or discontinuities can be located. The multi-scale or multi-resolution of signal analysis, which is the essence of wavelet transform, makes Wavelets popular in non-stationary signal analysis. In this paper, we present a Wavelet-LMS algorithm wherein the wavelet coefficients of a signal are modified adaptively using the Least Mean Square Algorithm and then reconstructed to give an Echo-free signal. The Echo Canceller based on this Algorithm is found to have a better convergence and a comparatively lesser MSE (Mean Square error).

Analysis and Improvement of Fireworks Algorithm

Directory of Open Access Journals (Sweden)

Xi-Guang Li

2017-02-01

Full Text Available The Fireworks Algorithm is a recently developed swarm intelligence algorithm to simulate the explosion process of fireworks. Based on the analysis of each operator of Fireworks Algorithm (FWA, this paper improves the FWA and proves that the improved algorithm converges to the global optimal solution with probability 1. The proposed algorithm improves the goal of further boosting performance and achieving global optimization where mainly include the following strategies. Firstly using the opposition-based learning initialization population. Secondly a new explosion amplitude mechanism for the optimal firework is proposed. In addition, the adaptive t-distribution mutation for non-optimal individuals and elite opposition-based learning for the optimal individual are used. Finally, a new selection strategy, namely Disruptive Selection, is proposed to reduce the running time of the algorithm compared with FWA. In our simulation, we apply the CEC2013 standard functions and compare the proposed algorithm (IFWA with SPSO2011, FWA, EFWA and dynFWA. The results show that the proposed algorithm has better overall performance on the test functions.

A dual communicator and dual grid-resolution algorithm for petascale simulations of turbulent mixing at high Schmidt number

Science.gov (United States)

Clay, M. P.; Buaria, D.; Gotoh, T.; Yeung, P. K.

2017-10-01

A new dual-communicator algorithm with very favorable performance characteristics has been developed for direct numerical simulation (DNS) of turbulent mixing of a passive scalar governed by an advection-diffusion equation. We focus on the regime of high Schmidt number (S c), where because of low molecular diffusivity the grid-resolution requirements for the scalar field are stricter than those for the velocity field by a factor √{ S c }. Computational throughput is improved by simulating the velocity field on a coarse grid of Nv3 points with a Fourier pseudo-spectral (FPS) method, while the passive scalar is simulated on a fine grid of Nθ3 points with a combined compact finite difference (CCD) scheme which computes first and second derivatives at eighth-order accuracy. A static three-dimensional domain decomposition and a parallel solution algorithm for the CCD scheme are used to avoid the heavy communication cost of memory transposes. A kernel is used to evaluate several approaches to optimize the performance of the CCD routines, which account for 60% of the overall simulation cost. On the petascale supercomputer Blue Waters at the University of Illinois, Urbana-Champaign, scalability is improved substantially with a hybrid MPI-OpenMP approach in which a dedicated thread per NUMA domain overlaps communication calls with computational tasks performed by a separate team of threads spawned using OpenMP nested parallelism. At a target production problem size of 81923 (0.5 trillion) grid points on 262,144 cores, CCD timings are reduced by 34% compared to a pure-MPI implementation. Timings for 163843 (4 trillion) grid points on 524,288 cores encouragingly maintain scalability greater than 90%, although the wall clock time is too high for production runs at this size. Performance monitoring with CrayPat for problem sizes up to 40963 shows that the CCD routines can achieve nearly 6% of the peak flop rate. The new DNS code is built upon two existing FPS and CCD codes

Empirical study of parallel LRU simulation algorithms

Science.gov (United States)

Carr, Eric; Nicol, David M.

1994-01-01

This paper reports on the performance of five parallel algorithms for simulating a fully associative cache operating under the LRU (Least-Recently-Used) replacement policy. Three of the algorithms are SIMD, and are implemented on the MasPar MP-2 architecture. Two other algorithms are parallelizations of an efficient serial algorithm on the Intel Paragon. One SIMD algorithm is quite simple, but its cost is linear in the cache size. The two other SIMD algorithm are more complex, but have costs that are independent on the cache size. Both the second and third SIMD algorithms compute all stack distances; the second SIMD algorithm is completely general, whereas the third SIMD algorithm presumes and takes advantage of bounds on the range of reference tags. Both MIMD algorithm implemented on the Paragon are general and compute all stack distances; they differ in one step that may affect their respective scalability. We assess the strengths and weaknesses of these algorithms as a function of problem size and characteristics, and compare their performance on traces derived from execution of three SPEC benchmark programs.

A Hybrid Chaotic Quantum Evolutionary Algorithm

DEFF Research Database (Denmark)

Cai, Y.; Zhang, M.; Cai, H.

2010-01-01

A hybrid chaotic quantum evolutionary algorithm is proposed to reduce amount of computation, speed up convergence and restrain premature phenomena of quantum evolutionary algorithm. The proposed algorithm adopts the chaotic initialization method to generate initial population which will form a pe...... tests. The presented algorithm is applied to urban traffic signal timing optimization and the effect is satisfied....

Reverse-time Migration in Tilted Transversely Isotropic Media with Decoupled Equations

KAUST Repository

Zhan, Ge

2012-12-01

benefit in cost saving of the new scheme, 2D and 3D RTM examples using the hybrid solution to the decoupled P-wave equation are carried out, and respective runtimes are listed and compared. Computation examples show that the hybrid strategy demands less computation time and is faster than using the pseudospectral method alone. Furthermore, this new hybrid TTI RTM algorithm is less computationally expensive than the FD solution to the conventional TTI coupled equations but more stable.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

International Nuclear Information System (INIS)

Cheng Sheng-Yi; Liu Wen-Jin; Chen Shan-Qiu; Dong Li-Zhi; Yang Ping; Xu Bing

2015-01-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n 2 ) ∼ O(n 3 ) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ∼ (O(n) 3/2 ), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. (paper)

The Parallel Algorithm Based on Genetic Algorithm for Improving the Performance of Cognitive Radio

Directory of Open Access Journals (Sweden)

Liu Miao

2018-01-01

Full Text Available The intercarrier interference (ICI problem of cognitive radio (CR is severe. In this paper, the machine learning algorithm is used to obtain the optimal interference subcarriers of an unlicensed user (un-LU. Masking the optimal interference subcarriers can suppress the ICI of CR. Moreover, the parallel ICI suppression algorithm is designed to improve the calculation speed and meet the practical requirement of CR. Simulation results show that the data transmission rate threshold of un-LU can be set, the data transmission quality of un-LU can be ensured, the ICI of a licensed user (LU is suppressed, and the bit error rate (BER performance of LU is improved by implementing the parallel suppression algorithm. The ICI problem of CR is solved well by the new machine learning algorithm. The computing performance of the algorithm is improved by designing a new parallel structure and the communication performance of CR is enhanced.

Look-ahead fermion algorithm

International Nuclear Information System (INIS)

Grady, M.

1986-01-01

I describe a fast fermion algorithm which utilizes pseudofermion fields but appears to have little or no systematic error. Test simulations on two-dimensional gauge theories are described. A possible justification for the algorithm being exact is discussed. 8 refs

Online co-regularized algorithms

NARCIS (Netherlands)

Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.

2012-01-01

We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks

Algorithmic complexity of quantum capacity

Science.gov (United States)

Oskouei, Samad Khabbazi; Mancini, Stefano

2018-04-01

We analyze the notion of quantum capacity from the perspective of algorithmic (descriptive) complexity. To this end, we resort to the concept of semi-computability in order to describe quantum states and quantum channel maps. We introduce algorithmic entropies (like algorithmic quantum coherent information) and derive relevant properties for them. Then we show that quantum capacity based on semi-computable concept equals the entropy rate of algorithmic coherent information, which in turn equals the standard quantum capacity. Thanks to this, we finally prove that the quantum capacity, for a given semi-computable channel, is limit computable.

Learning from nature: Nature-inspired algorithms

DEFF Research Database (Denmark)

Albeanu, Grigore; Madsen, Henrik; Popentiu-Vladicescu, Florin

2016-01-01

.), genetic and evolutionary strategies, artificial immune systems etc. Well-known examples of applications include: aircraft wing design, wind turbine design, bionic car, bullet train, optimal decisions related to traffic, appropriate strategies to survive under a well-adapted immune system etc. Based......During last decade, the nature has inspired researchers to develop new algorithms. The largest collection of nature-inspired algorithms is biology-inspired: swarm intelligence (particle swarm optimization, ant colony optimization, cuckoo search, bees' algorithm, bat algorithm, firefly algorithm etc...... on collective social behaviour of organisms, researchers have developed optimization strategies taking into account not only the individuals, but also groups and environment. However, learning from nature, new classes of approaches can be identified, tested and compared against already available algorithms...

Cache-Oblivious Algorithms and Data Structures

DEFF Research Database (Denmark)

Brodal, Gerth Stølting

2004-01-01

Frigo, Leiserson, Prokop and Ramachandran in 1999 introduced the ideal-cache model as a formal model of computation for developing algorithms in environments with multiple levels of caching, and coined the terminology of cache-oblivious algorithms. Cache-oblivious algorithms are described...... as standard RAM algorithms with only one memory level, i.e. without any knowledge about memory hierarchies, but are analyzed in the two-level I/O model of Aggarwal and Vitter for an arbitrary memory and block size and an optimal off-line cache replacement strategy. The result are algorithms that automatically...... apply to multi-level memory hierarchies. This paper gives an overview of the results achieved on cache-oblivious algorithms and data structures since the seminal paper by Frigo et al....

Portable Health Algorithms Test System

Science.gov (United States)

Melcher, Kevin J.; Wong, Edmond; Fulton, Christopher E.; Sowers, Thomas S.; Maul, William A.

2010-01-01

A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.

Algorithms

Indian Academy of Sciences (India)

algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).

Hardware Acceleration of Adaptive Neural Algorithms.

Energy Technology Data Exchange (ETDEWEB)

James, Conrad D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-11-01

As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - world conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.

Performance of Jet Algorithms in CMS

CERN Document Server

CMS Collaboration

The CMS Combined Software and Analysis Challenge 2007 (CSA07) is well underway and expected to produce a wealth of physics analyses to be applied to the first incoming detector data in 2008. The JetMET group of CMS supports four different jet clustering algorithms for the CSA07 Monte Carlo samples, with two different parameterizations each: \\fastkt, \\siscone, \\midpoint, and \\itcone. We present several studies comparing the performance of these algorithms using QCD dijet and \\ttbar Monte Carlo samples. We specifically observe that the \\siscone algorithm performs equal to or better than the \\midpoint algorithm in all presented studies and propose that \\siscone be adopted as the preferred cone-based jet clustering algorithm in future CMS physics analyses, as it is preferred by theorists for its infrared- and collinear-safety to all orders of perturbative QCD. We furthermore encourage the use of the \\fastkt algorithm which is found to perform as good as any other algorithm under study, features dramatically reduc...

Quantum-circuit model of Hamiltonian search algorithms

International Nuclear Information System (INIS)

Roland, Jeremie; Cerf, Nicolas J.

2003-01-01

We analyze three different quantum search algorithms, namely, the traditional circuit-based Grover's algorithm, its continuous-time analog by Hamiltonian evolution, and the quantum search by local adiabatic evolution. We show that these algorithms are closely related in the sense that they all perform a rotation, at a constant angular velocity, from a uniform superposition of all states to the solution state. This makes it possible to implement the two Hamiltonian-evolution algorithms on a conventional quantum circuit, while keeping the quadratic speedup of Grover's original algorithm. It also clarifies the link between the adiabatic search algorithm and Grover's algorithm

Algorithms for parallel computers

International Nuclear Information System (INIS)

Churchhouse, R.F.

1985-01-01

Until relatively recently almost all the algorithms for use on computers had been designed on the (usually unstated) assumption that they were to be run on single processor, serial machines. With the introduction of vector processors, array processors and interconnected systems of mainframes, minis and micros, however, various forms of parallelism have become available. The advantage of parallelism is that it offers increased overall processing speed but it also raises some fundamental questions, including: (i) which, if any, of the existing 'serial' algorithms can be adapted for use in the parallel mode. (ii) How close to optimal can such adapted algorithms be and, where relevant, what are the convergence criteria. (iii) How can we design new algorithms specifically for parallel systems. (iv) For multi-processor systems how can we handle the software aspects of the interprocessor communications. Aspects of these questions illustrated by examples are considered in these lectures. (orig.)

A hardware-algorithm co-design approach to optimize seizure detection algorithms for implantable applications.

Science.gov (United States)

Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P

2010-10-30

Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy. Copyright © 2010 Elsevier B.V. All rights reserved.

8. Algorithm Design Techniques

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 8. Algorithms - Algorithm Design Techniques. R K Shyamasundar. Series Article Volume 2 ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...

Efficient RNA structure comparison algorithms.

Science.gov (United States)

Arslan, Abdullah N; Anandan, Jithendar; Fry, Eric; Monschke, Keith; Ganneboina, Nitin; Bowerman, Jason

2017-12-01

Recently proposed relative addressing-based ([Formula: see text]) RNA secondary structure representation has important features by which an RNA structure database can be stored into a suffix array. A fast substructure search algorithm has been proposed based on binary search on this suffix array. Using this substructure search algorithm, we present a fast algorithm that finds the largest common substructure of given multiple RNA structures in [Formula: see text] format. The multiple RNA structure comparison problem is NP-hard in its general formulation. We introduced a new problem for comparing multiple RNA structures. This problem has more strict similarity definition and objective, and we propose an algorithm that solves this problem efficiently. We also develop another comparison algorithm that iteratively calls this algorithm to locate nonoverlapping large common substructures in compared RNAs. With the new resulting tools, we improved the RNASSAC website (linked from http://faculty.tamuc.edu/aarslan ). This website now also includes two drawing tools: one specialized for preparing RNA substructures that can be used as input by the search tool, and another one for automatically drawing the entire RNA structure from a given structure sequence.

Algorithms for worst-case tolerance optimization

DEFF Research Database (Denmark)

Schjær-Jacobsen, Hans; Madsen, Kaj

1979-01-01

New algorithms are presented for the solution of optimum tolerance assignment problems. The problems considered are defined mathematically as a worst-case problem (WCP), a fixed tolerance problem (FTP), and a variable tolerance problem (VTP). The basic optimization problem without tolerances...... is denoted the zero tolerance problem (ZTP). For solution of the WCP we suggest application of interval arithmetic and also alternative methods. For solution of the FTP an algorithm is suggested which is conceptually similar to algorithms previously developed by the authors for the ZTP. Finally, the VTP...... is solved by a double-iterative algorithm in which the inner iteration is performed by the FTP- algorithm. The application of the algorithm is demonstrated by means of relatively simple numerical examples. Basic properties, such as convergence properties, are displayed based on the examples....

Elementary functions algorithms and implementation

CERN Document Server

Muller, Jean-Michel

2016-01-01

This textbook presents the concepts and tools necessary to understand, build, and implement algorithms for computing elementary functions (e.g., logarithms, exponentials, and the trigonometric functions). Both hardware- and software-oriented algorithms are included, along with issues related to accurate floating-point implementation. This third edition has been updated and expanded to incorporate the most recent advances in the field, new elementary function algorithms, and function software. After a preliminary chapter that briefly introduces some fundamental concepts of computer arithmetic, such as floating-point arithmetic and redundant number systems, the text is divided into three main parts. Part I considers the computation of elementary functions using algorithms based on polynomial or rational approximations and using table-based methods; the final chapter in this section deals with basic principles of multiple-precision arithmetic. Part II is devoted to a presentation of “shift-and-add” algorithm...

Streaming Algorithms for Line Simplification

DEFF Research Database (Denmark)

Abam, Mohammad; de Berg, Mark; Hachenberger, Peter

2010-01-01

this problem in a streaming setting, where we only have a limited amount of storage, so that we cannot store all the points. We analyze the competitive ratio of our algorithms, allowing resource augmentation: we let our algorithm maintain a simplification with 2k (internal) points and compare the error of our...... simplification to the error of the optimal simplification with k points. We obtain the algorithms with O(1) competitive ratio for three cases: convex paths, where the error is measured using the Hausdorff distance (or Fréchet distance), xy-monotone paths, where the error is measured using the Hausdorff distance...... (or Fréchet distance), and general paths, where the error is measured using the Fréchet distance. In the first case the algorithm needs O(k) additional storage, and in the latter two cases the algorithm needs O(k 2) additional storage....

Advancements to the planogram frequency–distance rebinning algorithm

International Nuclear Information System (INIS)

Champley, Kyle M; Kinahan, Paul E; Raylman, Raymond R

2010-01-01

In this paper we consider the task of image reconstruction in positron emission tomography (PET) with the planogram frequency–distance rebinning (PFDR) algorithm. The PFDR algorithm is a rebinning algorithm for PET systems with panel detectors. The algorithm is derived in the planogram coordinate system which is a native data format for PET systems with panel detectors. A rebinning algorithm averages over the redundant four-dimensional set of PET data to produce a three-dimensional set of data. Images can be reconstructed from this rebinned three-dimensional set of data. This process enables one to reconstruct PET images more quickly than reconstructing directly from the four-dimensional PET data. The PFDR algorithm is an approximate rebinning algorithm. We show that implementing the PFDR algorithm followed by the (ramp) filtered backprojection (FBP) algorithm in linogram coordinates from multiple views reconstructs a filtered version of our image. We develop an explicit formula for this filter which can be used to achieve exact reconstruction by means of a modified FBP algorithm applied to the stack of rebinned linograms and can also be used to quantify the errors introduced by the PFDR algorithm. This filter is similar to the filter in the planogram filtered backprojection algorithm derived by Brasse et al. The planogram filtered backprojection and exact reconstruction with the PFDR algorithm require complete projections which can be completed with a reprojection algorithm. The PFDR algorithm is similar to the rebinning algorithm developed by Kao et al. By expressing the PFDR algorithm in detector coordinates, we provide a comparative analysis between the two algorithms. Numerical experiments using both simulated data and measured data from a positron emission mammography/tomography (PEM/PET) system are performed. Images are reconstructed by PFDR+FBP (PFDR followed by 2D FBP reconstruction), PFDRX (PFDR followed by the modified FBP algorithm for exact

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

Science.gov (United States)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Algorithmic alternatives

International Nuclear Information System (INIS)

Creutz, M.

1987-11-01

A large variety of Monte Carlo algorithms are being used for lattice gauge simulations. For purely bosonic theories, present approaches are generally adequate; nevertheless, overrelaxation techniques promise savings by a factor of about three in computer time. For fermionic fields the situation is more difficult and less clear. Algorithms which involve an extrapolation to a vanishing step size are all quite closely related. Methods which do not require such an approximation tend to require computer time which grows as the square of the volume of the system. Recent developments combining global accept/reject stages with Langevin or microcanonical updatings promise to reduce this growth to V/sup 4/3/

Estimates of radiation over clouds and dust aerosols: Optimized number of terms in phase function expansion

International Nuclear Information System (INIS)

Ding Shouguo; Xie Yu; Yang Ping; Weng Fuzhong; Liu Quanhua; Baum, Bryan; Hu Yongxiang

2009-01-01

The bulk-scattering properties of dust aerosols and clouds are computed for the community radiative transfer model (CRTM) that is a flagship effort of the Joint Center for Satellite Data Assimilation (JCSDA). The delta-fit method is employed to truncate the forward peaks of the scattering phase functions and to compute the Legendre expansion coefficients for re-constructing the truncated phase function. Use of more terms in the expansion gives more accurate re-construction of the phase function, but the issue remains as to how many terms are necessary for different applications. To explore this issue further, the bidirectional reflectances associated with dust aerosols, water clouds, and ice clouds are simulated with various numbers of Legendre expansion terms. To have relative numerical errors smaller than 5%, the present analyses indicate that, in the visible spectrum, 16 Legendre polynomials should be used for dust aerosols, while 32 Legendre expansion terms should be used for both water and ice clouds. In the infrared spectrum, the brightness temperatures at the top of the atmosphere are computed by using the scattering properties of dust aerosols, water clouds and ice clouds. Although small differences of brightness temperatures compared with the counterparts computed with 4, 8, 128 expansion terms are observed at large viewing angles for each layer, it is shown that 4 terms of Legendre polynomials are sufficient in the radiative transfer computation at infrared wavelengths for practical applications.

A Global algorithm for linear radiosity

OpenAIRE

Sbert Cassasayas, Mateu; Pueyo Sánchez, Xavier

1993-01-01

A linear algorithm for radiosity is presented, linear both in time and storage. The new algorithm is based on previous work by the authors and on the well known algorithms for progressive radiosity and Monte Carlo particle transport.

Algorithmic Mechanism Design of Evolutionary Computation.

Science.gov (United States)

Pei, Yan

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.

MultiAspect Graphs: Algebraic Representation and Algorithms

Directory of Open Access Journals (Sweden)

Klaus Wehmuth

2016-12-01

Full Text Available We present the algebraic representation and basic algorithms for MultiAspect Graphs (MAGs. A MAG is a structure capable of representing multilayer and time-varying networks, as well as higher-order networks, while also having the property of being isomorphic to a directed graph. In particular, we show that, as a consequence of the properties associated with the MAG structure, a MAG can be represented in matrix form. Moreover, we also show that any possible MAG function (algorithm can be obtained from this matrix-based representation. This is an important theoretical result since it paves the way for adapting well-known graph algorithms for application in MAGs. We present a set of basic MAG algorithms, constructed from well-known graph algorithms, such as degree computing, Breadth First Search (BFS, and Depth First Search (DFS. These algorithms adapted to the MAG context can be used as primitives for building other more sophisticated MAG algorithms. Therefore, such examples can be seen as guidelines on how to properly derive MAG algorithms from basic algorithms on directed graphs. We also make available Python implementations of all the algorithms presented in this paper.

Firefly Mating Algorithm for Continuous Optimization Problems

Directory of Open Access Journals (Sweden)

Amarita Ritthipakdee

2017-01-01

Full Text Available This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA, for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i the mutual attraction between males and females causes them to mate and (ii fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima.

Unconventional Algorithms: Complementarity of Axiomatics and Construction

Directory of Open Access Journals (Sweden)

Gordana Dodig Crnkovic

2012-10-01

Full Text Available In this paper, we analyze axiomatic and constructive issues of unconventional computations from a methodological and philosophical point of view. We explain how the new models of algorithms and unconventional computations change the algorithmic universe, making it open and allowing increased flexibility and expressive power that augment creativity. At the same time, the greater power of new types of algorithms also results in the greater complexity of the algorithmic universe, transforming it into the algorithmic multiverse and demanding new tools for its study. That is why we analyze new powerful tools brought forth by local mathematics, local logics, logical varieties and the axiomatic theory of algorithms, automata and computation. We demonstrate how these new tools allow efficient navigation in the algorithmic multiverse. Further work includes study of natural computation by unconventional algorithms and constructive approaches.

Integrated Association Rules Complete Hiding Algorithms

Directory of Open Access Journals (Sweden)

Mohamed Refaat Abdellah

2017-01-01

Full Text Available This paper presents database security approach for complete hiding of sensitive association rules by using six novel algorithms. These algorithms utilize three new weights to reduce the needed database modifications and support complete hiding, as well as they reduce the knowledge distortion and the data distortions. Complete weighted hiding algorithms enhance the hiding failure by 100%; these algorithms have the advantage of performing only a single scan for the database to gather the required information to form the hiding process. These proposed algorithms are built within the database structure which enables the sanitized database to be generated on run time as needed.

New Insights into the RLS Algorithm

Directory of Open Access Journals (Sweden)

Gänsler Tomas

2004-01-01

Full Text Available The recursive least squares (RLS algorithm is one of the most popular adaptive algorithms that can be found in the literature, due to the fact that it is easily and exactly derived from the normal equations. In this paper, we give another interpretation of the RLS algorithm and show the importance of linear interpolation error energies in the RLS structure. We also give a very efficient way to recursively estimate the condition number of the input signal covariance matrix thanks to fast versions of the RLS algorithm. Finally, we quantify the misalignment of the RLS algorithm with respect to the condition number.

Computational geometry algorithms and applications

CERN Document Server

de Berg, Mark; Overmars, Mark; Schwarzkopf, Otfried

1997-01-01

Computational geometry emerged from the field of algorithms design and anal­ ysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The suc­ cess of the field as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains--computer graphics, geographic in­ formation systems (GIS), robotics, and others-in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or difficult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simplified many of the previous approaches. In this textbook we have tried to make these modem algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can ...

Comparing Online Algorithms for Bin Packing Problems

DEFF Research Database (Denmark)

Epstein, Leah; Favrholdt, Lene Monrad; Kohrt, Jens Svalgaard

2012-01-01

The relative worst-order ratio is a measure of the quality of online algorithms. In contrast to the competitive ratio, this measure compares two online algorithms directly instead of using an intermediate comparison with an optimal offline algorithm. In this paper, we apply the relative worst-ord......-order ratio to online algorithms for several common variants of the bin packing problem. We mainly consider pairs of algorithms that are not distinguished by the competitive ratio and show that the relative worst-order ratio prefers the intuitively better algorithm of each pair....

Balancing the Power-to-Load Ratio for a Novel Variable Geometry Wave Energy Converter with Nonideal Power Take-Off in Regular Waves: Preprint

Energy Technology Data Exchange (ETDEWEB)

Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yu, Yi-Hsiang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wright, Alan D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-09-28

This work attempts to balance power absorption against structural loading for a novel variable geometry wave energy converter. The variable geometry consists of four identical flaps that will be opened in ascending order starting with the flap closest to the seafloor and moving to the free surface. The influence of a pitch motion constraint on power absorption when utilizing a nonideal power take-off (PTO) is examined and found to reduce the losses associated with bidirectional energy flow. The power-to-load ratio is evaluated using pseudo-spectral control to determine the optimum PTO torque based on a multiterm objective function. The pseudo-spectral optimal control problem is extended to include load metrics in the objective function, which may now consist of competing terms. Separate penalty weights are attached to the surge-foundation force and PTO control torque to tune the optimizer performance to emphasize either power absorption or load shedding. PTO efficiency is not included in the objective function, but the penalty weights are utilized to limit the force and torque amplitudes, thereby reducing losses associated with bidirectional energy flow. Results from pseudo-spectral control demonstrate that shedding a portion of the available wave energy can provide greater reductions in structural loads and reactive power.

Algorithms

Indian Academy of Sciences (India)

algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...

Empirical tests of the Gradual Learning Algorithm

NARCIS (Netherlands)

Boersma, P.; Hayes, B.

1999-01-01

The Gradual Learning Algorithm (Boersma 1997) is a constraint ranking algorithm for learning Optimality-theoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and

Empirical tests of the Gradual Learning Algorithm

NARCIS (Netherlands)

Boersma, P.; Hayes, B.

2001-01-01

The Gradual Learning Algorithm (Boersma 1997) is a constraint-ranking algorithm for learning optimality-theoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and

Deterministic algorithms for multi-criteria Max-TSP

NARCIS (Netherlands)

Manthey, Bodo

2012-01-01

We present deterministic approximation algorithms for the multi-criteria maximum traveling salesman problem (Max-TSP). Our algorithms are faster and simpler than the existing randomized algorithms. We devise algorithms for the symmetric and asymmetric multi-criteria Max-TSP that achieve ratios of

Verification-Based Interval-Passing Algorithm for Compressed Sensing

OpenAIRE

Wu, Xiaofu; Yang, Zhen

2013-01-01

We propose a verification-based Interval-Passing (IP) algorithm for iteratively reconstruction of nonnegative sparse signals using parity check matrices of low-density parity check (LDPC) codes as measurement matrices. The proposed algorithm can be considered as an improved IP algorithm by further incorporation of the mechanism of verification algorithm. It is proved that the proposed algorithm performs always better than either the IP algorithm or the verification algorithm. Simulation resul...

Multimodal Estimation of Distribution Algorithms.

Science.gov (United States)

Yang, Qiang; Chen, Wei-Neng; Li, Yun; Chen, C L Philip; Xu, Xiang-Min; Zhang, Jun

2016-02-15

Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima.

Algorithms and Their Explanations

NARCIS (Netherlands)

Benini, M.; Gobbo, F.; Beckmann, A.; Csuhaj-Varjú, E.; Meer, K.

2014-01-01

By analysing the explanation of the classical heapsort algorithm via the method of levels of abstraction mainly due to Floridi, we give a concrete and precise example of how to deal with algorithmic knowledge. To do so, we introduce a concept already implicit in the method, the ‘gradient of

Engineering a Cache-Oblivious Sorting Algorithm

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Fagerberg, Rolf; Vinther, Kristoffer

2007-01-01

This paper is an algorithmic engineering study of cache-oblivious sorting. We investigate by empirical methods a number of implementation issues and parameter choices for the cache-oblivious sorting algorithm Lazy Funnelsort, and compare the final algorithm with Quicksort, the established standard...

On the efficiency of treating singularities in triatomic variational vibrational computations. The vibrational states of H(+)3 up to dissociation.

Science.gov (United States)

Szidarovszky, Tamás; Császár, Attila G; Czakó, Gábor

2010-08-01

Several techniques of varying efficiency are investigated, which treat all singularities present in the triatomic vibrational kinetic energy operator given in orthogonal internal coordinates of the two distances-one angle type. The strategies are based on the use of a direct-product basis built from one-dimensional discrete variable representation (DVR) bases corresponding to the two distances and orthogonal Legendre polynomials, or the corresponding Legendre-DVR basis, corresponding to the angle. The use of Legendre functions ensures the efficient treatment of the angular singularity. Matrix elements of the singular radial operators are calculated employing DVRs using the quadrature approximation as well as special DVRs satisfying the boundary conditions and thus allowing for the use of exact DVR expressions. Potential optimized (PO) radial DVRs, based on one-dimensional Hamiltonians with potentials obtained by fixing or relaxing the two non-active coordinates, are also studied. The numerical calculations employed Hermite-DVR, spherical-oscillator-DVR, and Bessel-DVR bases as the primitive radial functions. A new analytical formula is given for the determination of the matrix elements of the singular radial operator using the Bessel-DVR basis. The usually claimed failure of the quadrature approximation in certain singular integrals is revisited in one and three dimensions. It is shown that as long as no potential optimization is carried out the quadrature approximation works almost as well as the exact DVR expressions. If wave functions with finite amplitude at the boundary are to be computed, the basis sets need to meet the required boundary conditions. The present numerical results also confirm that PO-DVRs should be constructed employing relaxed potentials and PO-DVRs can be useful for optimizing quadrature points for calculations applying large coordinate intervals and describing large-amplitude motions. The utility and efficiency of the different algorithms

PROPOSAL OF ALGORITHM FOR ROUTE OPTIMIZATION

OpenAIRE

Robert Ramon de Carvalho Sousa; Abimael de Jesus Barros Costa; Eliezé Bulhões de Carvalho; Adriano de Carvalho Paranaíba; Daylyne Maerla Gomes Lima Sandoval

2016-01-01

This article uses “Six Sigma” methodology for the elaboration of an algorithm for routing problems which is able to obtain more efficient results than those from Clarke and Wright´s (CW) algorithm (1964) in situations of random increase of product delivery demands, facing the incapability of service level increase . In some situations, the algorithm proposed obtained more efficient results than the CW algorithm. The key factor was a reduction in the number of mistakes (on...

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

Principal component analysis networks and algorithms

CERN Document Server

Kong, Xiangyu; Duan, Zhansheng

2017-01-01

This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.

FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS

Directory of Open Access Journals (Sweden)

Evans BAIDOO

2017-03-01

Full Text Available Modern real world science and engineering problems can be classified as multi-objective optimisation problems which demand for expedient and efficient stochastic algorithms to respond to the optimization needs. This paper presents an object-oriented software application that implements a firework optimization algorithm for function optimization problems. The algorithm, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard benchmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended experimentation. Additionally, this paper validates the effect of runtime on the algorithm performance.

A Cavity QED Implementation of Deutsch-Jozsa Algorithm

OpenAIRE

Guerra, E. S.

2004-01-01

The Deutsch-Jozsa algorithm is a generalization of the Deutsch algorithm which was the first algorithm written. We present schemes to implement the Deutsch algorithm and the Deutsch-Jozsa algorithm via cavity QED.

A pipelined FPGA implementation of an encryption algorithm based on genetic algorithm

Science.gov (United States)

Thirer, Nonel

2013-05-01

With the evolution of digital data storage and exchange, it is essential to protect the confidential information from every unauthorized access. High performance encryption algorithms were developed and implemented by software and hardware. Also many methods to attack the cipher text were developed. In the last years, the genetic algorithm has gained much interest in cryptanalysis of cipher texts and also in encryption ciphers. This paper analyses the possibility to use the genetic algorithm as a multiple key sequence generator for an AES (Advanced Encryption Standard) cryptographic system, and also to use a three stages pipeline (with four main blocks: Input data, AES Core, Key generator, Output data) to provide a fast encryption and storage/transmission of a large amount of data.

A Parallel Butterfly Algorithm

KAUST Repository

Poulson, Jack; Demanet, Laurent; Maxwell, Nicholas; Ying, Lexing

2014-01-01

The butterfly algorithm is a fast algorithm which approximately evaluates a discrete analogue of the integral transform (Equation Presented.) at large numbers of target points when the kernel, K(x, y), is approximately low-rank when restricted to subdomains satisfying a certain simple geometric condition. In d dimensions with O(Nd) quasi-uniformly distributed source and target points, when each appropriate submatrix of K is approximately rank-r, the running time of the algorithm is at most O(r2Nd logN). A parallelization of the butterfly algorithm is introduced which, assuming a message latency of α and per-process inverse bandwidth of β, executes in at most (Equation Presented.) time using p processes. This parallel algorithm was then instantiated in the form of the open-source DistButterfly library for the special case where K(x, y) = exp(iΦ(x, y)), where Φ(x, y) is a black-box, sufficiently smooth, real-valued phase function. Experiments on Blue Gene/Q demonstrate impressive strong-scaling results for important classes of phase functions. Using quasi-uniform sources, hyperbolic Radon transforms, and an analogue of a three-dimensional generalized Radon transform were, respectively, observed to strong-scale from 1-node/16-cores up to 1024-nodes/16,384-cores with greater than 90% and 82% efficiency, respectively. © 2014 Society for Industrial and Applied Mathematics.

A Parallel Butterfly Algorithm

KAUST Repository

Poulson, Jack

2014-02-04

The butterfly algorithm is a fast algorithm which approximately evaluates a discrete analogue of the integral transform (Equation Presented.) at large numbers of target points when the kernel, K(x, y), is approximately low-rank when restricted to subdomains satisfying a certain simple geometric condition. In d dimensions with O(Nd) quasi-uniformly distributed source and target points, when each appropriate submatrix of K is approximately rank-r, the running time of the algorithm is at most O(r2Nd logN). A parallelization of the butterfly algorithm is introduced which, assuming a message latency of α and per-process inverse bandwidth of β, executes in at most (Equation Presented.) time using p processes. This parallel algorithm was then instantiated in the form of the open-source DistButterfly library for the special case where K(x, y) = exp(iΦ(x, y)), where Φ(x, y) is a black-box, sufficiently smooth, real-valued phase function. Experiments on Blue Gene/Q demonstrate impressive strong-scaling results for important classes of phase functions. Using quasi-uniform sources, hyperbolic Radon transforms, and an analogue of a three-dimensional generalized Radon transform were, respectively, observed to strong-scale from 1-node/16-cores up to 1024-nodes/16,384-cores with greater than 90% and 82% efficiency, respectively. © 2014 Society for Industrial and Applied Mathematics.

One improved LSB steganography algorithm

Science.gov (United States)

Song, Bing; Zhang, Zhi-hong

2013-03-01

It is easy to be detected by X2 and RS steganalysis with high accuracy that using LSB algorithm to hide information in digital image. We started by selecting information embedded location and modifying the information embedded method, combined with sub-affine transformation and matrix coding method, improved the LSB algorithm and a new LSB algorithm was proposed. Experimental results show that the improved one can resist the X2 and RS steganalysis effectively.

Graph Algorithm Animation with Grrr

OpenAIRE

Rodgers, Peter; Vidal, Natalia

2000-01-01

We discuss geometric positioning, highlighting of visited nodes and user defined highlighting that form the algorithm animation facilities in the Grrr graph rewriting programming language. The main purpose of animation was initially for the debugging and profiling of Grrr code, but recently it has been extended for the purpose of teaching algorithms to undergraduate students. The animation is restricted to graph based algorithms such as graph drawing, list manipulation or more traditional gra...

Algorithms over partially ordered sets

DEFF Research Database (Denmark)

Baer, Robert M.; Østerby, Ole

1969-01-01

in partially ordered sets, answer the combinatorial question of how many maximal chains might exist in a partially ordered set withn elements, and we give an algorithm for enumerating all maximal chains. We give (in § 3) algorithms which decide whether a partially ordered set is a (lower or upper) semi......-lattice, and whether a lattice has distributive, modular, and Boolean properties. Finally (in § 4) we give Algol realizations of the various algorithms....

A generalization of Takane's algorithm for DEDICOM

NARCIS (Netherlands)

Kiers, Henk A.L.; ten Berge, Jos M.F.; Takane, Yoshio; de Leeuw, Jan

An algorithm is described for fitting the DEDICOM model for the analysis of asymmetric data matrices. This algorithm generalizes an algorithm suggested by Takane in that it uses a damping parameter in the iterative process. Takane's algorithm does not always converge monotonically. Based on the

Integrating Algorithm Visualization Video into a First-Year Algorithm and Data Structure Course

Science.gov (United States)

Crescenzi, Pilu; Malizia, Alessio; Verri, M. Cecilia; Diaz, Paloma; Aedo, Ignacio

2012-01-01

In this paper we describe the results that we have obtained while integrating algorithm visualization (AV) movies (strongly tightened with the other teaching material), within a first-year undergraduate course on algorithms and data structures. Our experimental results seem to support the hypothesis that making these movies available significantly…

The Algorithm of Link Prediction on Social Network

Directory of Open Access Journals (Sweden)

Liyan Dong

2013-01-01

Full Text Available At present, most link prediction algorithms are based on the similarity between two entities. Social network topology information is one of the main sources to design the similarity function between entities. But the existing link prediction algorithms do not apply the network topology information sufficiently. For lack of traditional link prediction algorithms, we propose two improved algorithms: CNGF algorithm based on local information and KatzGF algorithm based on global information network. For the defect of the stationary of social network, we also provide the link prediction algorithm based on nodes multiple attributes information. Finally, we verified these algorithms on DBLP data set, and the experimental results show that the performance of the improved algorithm is superior to that of the traditional link prediction algorithm.

Algorithmic Self

DEFF Research Database (Denmark)

Markham, Annette

This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....

Discrete Riccati equation solutions: Distributed algorithms

Directory of Open Access Journals (Sweden)

D. G. Lainiotis

1996-01-01

Full Text Available In this paper new distributed algorithms for the solution of the discrete Riccati equation are introduced. The algorithms are used to provide robust and computational efficient solutions to the discrete Riccati equation. The proposed distributed algorithms are theoretically interesting and computationally attractive.

A Hybrid Algorithm for Optimizing Multi- Modal Functions

Institute of Scientific and Technical Information of China (English)

Li Qinghua; Yang Shida; Ruan Youlin

2006-01-01

A new genetic algorithm is presented based on the musical performance. The novelty of this algorithm is that a new genetic algorithm, mimicking the musical process of searching for a perfect state of harmony, which increases the robustness of it greatly and gives a new meaning of it in the meantime, has been developed. Combining the advantages of the new genetic algorithm, simplex algorithm and tabu search, a hybrid algorithm is proposed. In order to verify the effectiveness of the hybrid algorithm, it is applied to solving some typical numerical function optimization problems which are poorly solved by traditional genetic algorithms. The experimental results show that the hybrid algorithm is fast and reliable.

Fast algorithm of adaptive Fourier series

Science.gov (United States)

Gao, You; Ku, Min; Qian, Tao

2018-05-01

Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in particular, motivated the so-called pre-orthogonal greedy algorithm (Pre-OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper offers one formulation of the 1-D AFD algorithm by building the FFT algorithm into it. Accordingly, the algorithm complexity is reduced, from the original $\\mathcal{O}(M N^2)$ to $\\mathcal{O}(M N\\log_2 N)$, where $N$ denotes the number of the discretization points on the unit circle and $M$ denotes the number of points in $[0,1)$. This greatly enhances the applicability of AFD. Experiments are carried out to show the high efficiency of the proposed algorithm.

Modified Decoding Algorithm of LLR-SPA

Directory of Open Access Journals (Sweden)

Zhongxun Wang

2014-09-01

Full Text Available In wireless sensor networks, the energy consumption is mainly occurred in the stage of information transmission. The Low Density Parity Check code can make full use of the channel information to save energy. Because of the widely used decoding algorithm of the Low Density Parity Check code, this paper proposes a new decoding algorithm which is based on the LLR-SPA (Sum-Product Algorithm in Log-Likelihood-domain to improve the accuracy of the decoding algorithm. In the modified algorithm, a piecewise linear function is used to approximate the complicated Jacobi correction term in LLR-SPA decoding algorithm. Construct the tangent by the tangency point to the function of Jacobi correction term, which is based on the first order Taylor Series. In this way, the proposed piecewise linear approximation offers almost a perfect match to the function of Jacobi correction term. Meanwhile, the proposed piecewise linear approximation could avoid the operation of logarithmic which is more suitable for practical application. The simulation results show that the proposed algorithm could improve the decoding accuracy greatly without noticeable variation of the computational complexity.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

Science.gov (United States)

Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing

2015-08-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).

Planar graphs theory and algorithms

CERN Document Server

Nishizeki, T

1988-01-01

Collected in this volume are most of the important theorems and algorithms currently known for planar graphs, together with constructive proofs for the theorems. Many of the algorithms are written in Pidgin PASCAL, and are the best-known ones; the complexities are linear or 0(nlogn). The first two chapters provide the foundations of graph theoretic notions and algorithmic techniques. The remaining chapters discuss the topics of planarity testing, embedding, drawing, vertex- or edge-coloring, maximum independence set, subgraph listing, planar separator theorem, Hamiltonian cycles, and single- or multicommodity flows. Suitable for a course on algorithms, graph theory, or planar graphs, the volume will also be useful for computer scientists and graph theorists at the research level. An extensive reference section is included.

Comprehensive asynchronous symmetric rendezvous algorithm in ...

Indian Academy of Sciences (India)

Meenu Chawla

2017-11-10

Nov 10, 2017 ... Simulation results affirm that CASR algorithm performs better in terms of average time-to-rendezvous as compared ... process; neighbour discovery; symmetric rendezvous algorithm. 1. .... dezvous in finite time under the symmetric model. The CH ..... CASR algorithm in Matlab 7.11 and performed several.

Learning algorithms and automatic processing of languages

International Nuclear Information System (INIS)

Fluhr, Christian Yves Andre

1977-01-01

This research thesis concerns the field of artificial intelligence. It addresses learning algorithms applied to automatic processing of languages. The author first briefly describes some mechanisms of human intelligence in order to describe how these mechanisms are simulated on a computer. He outlines the specific role of learning in various manifestations of intelligence. Then, based on the Markov's algorithm theory, the author discusses the notion of learning algorithm. Two main types of learning algorithms are then addressed: firstly, an 'algorithm-teacher dialogue' type sanction-based algorithm which aims at learning how to solve grammatical ambiguities in submitted texts; secondly, an algorithm related to a document system which structures semantic data automatically obtained from a set of texts in order to be able to understand by references to any question on the content of these texts

Using Alternative Multiplication Algorithms to "Offload" Cognition

Science.gov (United States)

Jazby, Dan; Pearn, Cath

2015-01-01

When viewed through a lens of embedded cognition, algorithms may enable aspects of the cognitive work of multi-digit multiplication to be "offloaded" to the environmental structure created by an algorithm. This study analyses four multiplication algorithms by viewing different algorithms as enabling cognitive work to be distributed…

Named Entity Linking Algorithm

Directory of Open Access Journals (Sweden)

M. F. Panteleev

2017-01-01

Full Text Available In the tasks of processing text in natural language, Named Entity Linking (NEL represents the task to define and link some entity, which is found in the text, with some entity in the knowledge base (for example, Dbpedia. Currently, there is a diversity of approaches to solve this problem, but two main classes can be identified: graph-based approaches and machine learning-based ones. Graph and Machine Learning approaches-based algorithm is proposed accordingly to the stated assumptions about the interrelations of named entities in a sentence and in general.In the case of graph-based approaches, it is necessary to solve the problem of identifying an optimal set of the related entities according to some metric that characterizes the distance between these entities in a graph built on some knowledge base. Due to limitations in processing power, to solve this task directly is impossible. Therefore, its modification is proposed. Based on the algorithms of machine learning, an independent solution cannot be built due to small volumes of training datasets relevant to NEL task. However, their use can contribute to improving the quality of the algorithm. The adaptation of the Latent Dirichlet Allocation model is proposed in order to obtain a measure of the compatibility of attributes of various entities encountered in one context.The efficiency of the proposed algorithm was experimentally tested. A test dataset was independently generated. On its basis the performance of the model was compared using the proposed algorithm with the open source product DBpedia Spotlight, which solves the NEL problem.The mockup, based on the proposed algorithm, showed a low speed as compared to DBpedia Spotlight. However, the fact that it has shown higher accuracy, stipulates the prospects for work in this direction.The main directions of development were proposed in order to increase the accuracy of the system and its productivity.

Algorithm 426 : Merge sort algorithm [M1

NARCIS (Netherlands)

Bron, C.

1972-01-01

Sorting by means of a two-way merge has a reputation of requiring a clerically complicated and cumbersome program. This ALGOL 60 procedure demonstrates that, using recursion, an elegant and efficient algorithm can be designed, the correctness of which is easily proved [2]. Sorting n objects gives

Wavefront-ray grid FDTD algorithm

OpenAIRE

ÇİYDEM, MEHMET

2016-01-01

A finite difference time domain algorithm on a wavefront-ray grid (WRG-FDTD) is proposed in this study to reduce numerical dispersion of conventional FDTD methods. A FDTD algorithm conforming to a wavefront-ray grid can be useful to take into account anisotropy effects of numerical grids since it features directional energy flow along the rays. An explicit and second-order accurate WRG-FDTD algorithm is provided in generalized curvilinear coordinates for an inhomogeneous isotropic medium. Num...

Unsupervised Classification Using Immune Algorithm

OpenAIRE

Al-Muallim, M. T.; El-Kouatly, R.

2012-01-01

Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed U...

A Novel Optimal Control Method for Impulsive-Correction Projectile Based on Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Ruisheng Sun

2016-01-01

Full Text Available This paper presents a new parametric optimization approach based on a modified particle swarm optimization (PSO to design a class of impulsive-correction projectiles with discrete, flexible-time interval, and finite-energy control. In terms of optimal control theory, the task is described as the formulation of minimum working number of impulses and minimum control error, which involves reference model linearization, boundary conditions, and discontinuous objective function. These result in difficulties in finding the global optimum solution by directly utilizing any other optimization approaches, for example, Hp-adaptive pseudospectral method. Consequently, PSO mechanism is employed for optimal setting of impulsive control by considering the time intervals between two neighboring lateral impulses as design variables, which makes the briefness of the optimization process. A modification on basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. In addition, a suboptimal control and guidance law based on PSO technique are put forward for the real-time consideration of the online design in practice. Finally, a simulation case coupled with a nonlinear flight dynamic model is applied to validate the modified PSO control algorithm. The results of comparative study illustrate that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately and provides a reference approach to handling such impulsive-correction problem.

Hybrid employment recommendation algorithm based on Spark

Science.gov (United States)

Li, Zuoquan; Lin, Yubei; Zhang, Xingming

2017-08-01

Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.

Evaluation Of Algorithms Of Anti- HIV Antibody Tests

Directory of Open Access Journals (Sweden)

Paranjape R.S

1997-01-01

Full Text Available Research question: Can alternate algorithms be used in place of conventional algorithm for epidemiological studies of HIV infection with less expenses? Objective: To compare the results of HIV sero- prevalence as determined by test algorithms combining three kits with conventional test algorithm. Study design: Cross â€" sectional. Participants: 282 truck drivers. Statistical analysis: Sensitivity and specificity analysis and predictive values. Results: Three different algorithms that do not include Western Blot (WB were compared with the conventional algorithm, in a truck driver population with 5.6% prevalence of HIV â€"I infection. Algorithms with one EIA (Genetic Systems or Biotest and a rapid test (immunocomb or with two EIAs showed 100% positive predictive value in relation to the conventional algorithm. Using an algorithm with EIA as screening test and a rapid test as a confirmatory test was 50 to 70% less expensive than the conventional algorithm per positive scrum sample. These algorithms obviate the interpretation of indeterminate results and also give differential diagnosis of HIV-2 infection. Alternate algorithms are ideally suited for community based control programme in developing countries. Application of these algorithms in population with low prevalence should also be studied in order to evaluate universal applicability.

Categorizing Variations of Student-Implemented Sorting Algorithms

Science.gov (United States)

Taherkhani, Ahmad; Korhonen, Ari; Malmi, Lauri

2012-01-01

In this study, we examined freshmen students' sorting algorithm implementations in data structures and algorithms' course in two phases: at the beginning of the course before the students received any instruction on sorting algorithms, and after taking a lecture on sorting algorithms. The analysis revealed that many students have insufficient…

Decoding Hermitian Codes with Sudan's Algorithm

DEFF Research Database (Denmark)

Høholdt, Tom; Nielsen, Rasmus Refslund

1999-01-01

We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q-polynomial, and a reduct......We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q...

Decoding algorithm for vortex communications receiver

Science.gov (United States)

Kupferman, Judy; Arnon, Shlomi

2018-01-01

Vortex light beams can provide a tremendous alphabet for encoding information. We derive a symbol decoding algorithm for a direct detection matrix detector vortex beam receiver using Laguerre Gauss (LG) modes, and develop a mathematical model of symbol error rate (SER) for this receiver. We compare SER as a function of signal to noise ratio (SNR) for our algorithm and for the Pearson correlation algorithm. To our knowledge, this is the first comprehensive treatment of a decoding algorithm of a matrix detector for an LG receiver.

Quantum algorithms for testing Boolean functions

Directory of Open Access Journals (Sweden)

Erika Andersson

2010-06-01

Full Text Available We discuss quantum algorithms, based on the Bernstein-Vazirani algorithm, for finding which variables a Boolean function depends on. There are 2^n possible linear Boolean functions of n variables; given a linear Boolean function, the Bernstein-Vazirani quantum algorithm can deterministically identify which one of these Boolean functions we are given using just one single function query. The same quantum algorithm can also be used to learn which input variables other types of Boolean functions depend on, with a success probability that depends on the form of the Boolean function that is tested, but does not depend on the total number of input variables. We also outline a procedure to futher amplify the success probability, based on another quantum algorithm, the Grover search.

[An improved algorithm for electrohysterogram envelope extraction].

Science.gov (United States)

Lu, Yaosheng; Pan, Jie; Chen, Zhaoxia; Chen, Zhaoxia

2017-02-01

Extraction uterine contraction signal from abdominal uterine electromyogram(EMG) signal is considered as the most promising method to replace the traditional tocodynamometer(TOCO) for detecting uterine contractions activity. The traditional root mean square(RMS) algorithm has only some limited values in canceling the impulsive noise. In our study, an improved algorithm for uterine EMG envelope extraction was proposed to overcome the problem. Firstly, in our experiment, zero-crossing detection method was used to separate the burst of uterine electrical activity from the raw uterine EMG signal. After processing the separated signals by employing two filtering windows which have different width, we used the traditional RMS algorithm to extract uterus EMG envelope. To assess the performance of the algorithm, the improved algorithm was compared with two existing intensity of uterine electromyogram(IEMG) extraction algorithms. The results showed that the improved algorithm was better than the traditional ones in eliminating impulsive noise present in the uterine EMG signal. The measurement sensitivity and positive predictive value(PPV) of the improved algorithm were 0.952 and 0.922, respectively, which were not only significantly higher than the corresponding values(0.859 and 0.847) of the first comparison algorithm, but also higher than the values(0.928 and 0.877) of the second comparison algorithm. Thus the new method is reliable and effective.

Legendre's and Kummer's Theorems Again

Indian Academy of Sciences (India)

tember 1895. Gazeta Mate- matica was a true school of math- ematics, that contributed to the formation of many generations of young math enthusiasts. Al- most all romanian mathemati- cians were collaborators of. Gazeta. 2.3 A Useful Inequality. From vp(n!) = n¡sp(n) p¡1 the following useful inequality immediately follows:.

Recursive automatic classification algorithms

Energy Technology Data Exchange (ETDEWEB)

Bauman, E V; Dorofeyuk, A A

1982-03-01

A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.

Seamless Merging of Hypertext and Algorithm Animation

Science.gov (United States)

Karavirta, Ville

2009-01-01

Online learning material that students use by themselves is one of the typical usages of algorithm animation (AA). Thus, the integration of algorithm animations into hypertext is seen as an important topic today to promote the usage of algorithm animation in teaching. This article presents an algorithm animation viewer implemented purely using…

Dissipative Structures of the Kuramoto–Sivashinsky Equation

Directory of Open Access Journals (Sweden)

N. A. Kudryashov

2015-01-01

Full Text Available In the present work, we study the features of dissipative structures formation described by the periodic boundary value problem for the Kuramoto-Sivashinsky equation. The numerical algorithm which is based on the pseudospectral method is presented. We prove the efficiency and accuracy of the proposed numerical method on the exact solution of the equation considered. Using this approach, we performed the numerical simulation of dissipative structure formations described by the Kuramoto–Sivashinsky equation. The influence of the problem parameters on these processes are studied. The quantitative and qualitative characteristics of dissipative structure formations are described. We have shown that there is a value of the control parameter at which the processes of dissipative structure formation are observed. In particular, using the cyclic convolution we define the average value of this parameter. Also, we find the dependence of the amplitude of the structures on the value of control parameter.

Binar Sort: A Linear Generalized Sorting Algorithm

OpenAIRE

Gilreath, William F.

2008-01-01

Sorting is a common and ubiquitous activity for computers. It is not surprising that there exist a plethora of sorting algorithms. For all the sorting algorithms, it is an accepted performance limit that sorting algorithms are linearithmic or O(N lg N). The linearithmic lower bound in performance stems from the fact that the sorting algorithms use the ordering property of the data. The sorting algorithm uses comparison by the ordering property to arrange the data elements from an initial perm...

On König's root finding algorithms

DEFF Research Database (Denmark)

Buff, Xavier; Henriksen, Christian

2003-01-01

In this paper, we first recall the definition of a family of root-finding algorithms known as König's algorithms. We establish some local and some global properties of those algorithms. We give a characterization of rational maps which arise as König's methods of polynomials with simple roots. We...

Adaptive discrete-ordinates algorithms and strategies

International Nuclear Information System (INIS)

Stone, J.C.; Adams, M.L.

2005-01-01

We present our latest algorithms and strategies for adaptively refined discrete-ordinates quadrature sets. In our basic strategy, which we apply here in two-dimensional Cartesian geometry, the spatial domain is divided into regions. Each region has its own quadrature set, which is adapted to the region's angular flux. Our algorithms add a 'test' direction to the quadrature set if the angular flux calculated at that direction differs by more than a user-specified tolerance from the angular flux interpolated from other directions. Different algorithms have different prescriptions for the method of interpolation and/or choice of test directions and/or prescriptions for quadrature weights. We discuss three different algorithms of different interpolation orders. We demonstrate through numerical results that each algorithm is capable of generating solutions with negligible angular discretization error. This includes elimination of ray effects. We demonstrate that all of our algorithms achieve a given level of error with far fewer unknowns than does a standard quadrature set applied to an entire problem. To address a potential issue with other algorithms, we present one algorithm that retains exact integration of high-order spherical-harmonics functions, no matter how much local refinement takes place. To address another potential issue, we demonstrate that all of our methods conserve partial currents across interfaces where quadrature sets change. We conclude that our approach is extremely promising for solving the long-standing problem of angular discretization error in multidimensional transport problems. (authors)

Multicore and GPU algorithms for Nussinov RNA folding

Science.gov (United States)

2014-01-01

Background One segment of a RNA sequence might be paired with another segment of the same RNA sequence due to the force of hydrogen bonds. This two-dimensional structure is called the RNA sequence's secondary structure. Several algorithms have been proposed to predict an RNA sequence's secondary structure. These algorithms are referred to as RNA folding algorithms. Results We develop cache efficient, multicore, and GPU algorithms for RNA folding using Nussinov's algorithm. Conclusions Our cache efficient algorithm provides a speedup between 1.6 and 3.0 relative to a naive straightforward single core code. The multicore version of the cache efficient single core algorithm provides a speedup, relative to the naive single core algorithm, between 7.5 and 14.0 on a 6 core hyperthreaded CPU. Our GPU algorithm for the NVIDIA C2050 is up to 1582 times as fast as the naive single core algorithm and between 5.1 and 11.2 times as fast as the fastest previously known GPU algorithm for Nussinov RNA folding. PMID:25082539

Optimal Pid Controller Design Using Adaptive Vurpso Algorithm

Science.gov (United States)

Zirkohi, Majid Moradi

2015-04-01

The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.

Array architectures for iterative algorithms

Science.gov (United States)

Jagadish, Hosagrahar V.; Rao, Sailesh K.; Kailath, Thomas

1987-01-01

Regular mesh-connected arrays are shown to be isomorphic to a class of so-called regular iterative algorithms. For a wide variety of problems it is shown how to obtain appropriate iterative algorithms and then how to translate these algorithms into arrays in a systematic fashion. Several 'systolic' arrays presented in the literature are shown to be specific cases of the variety of architectures that can be derived by the techniques presented here. These include arrays for Fourier Transform, Matrix Multiplication, and Sorting.

Testing block subdivision algorithms on block designs

Science.gov (United States)

Wiseman, Natalie; Patterson, Zachary

2016-01-01

Integrated land use-transportation models predict future transportation demand taking into account how households and firms arrange themselves partly as a function of the transportation system. Recent integrated models require parcels as inputs and produce household and employment predictions at the parcel scale. Block subdivision algorithms automatically generate parcel patterns within blocks. Evaluating block subdivision algorithms is done by way of generating parcels and comparing them to those in a parcel database. Three block subdivision algorithms are evaluated on how closely they reproduce parcels of different block types found in a parcel database from Montreal, Canada. While the authors who developed each of the algorithms have evaluated them, they have used their own metrics and block types to evaluate their own algorithms. This makes it difficult to compare their strengths and weaknesses. The contribution of this paper is in resolving this difficulty with the aim of finding a better algorithm suited to subdividing each block type. The proposed hypothesis is that given the different approaches that block subdivision algorithms take, it's likely that different algorithms are better adapted to subdividing different block types. To test this, a standardized block type classification is used that consists of mutually exclusive and comprehensive categories. A statistical method is used for finding a better algorithm and the probability it will perform well for a given block type. Results suggest the oriented bounding box algorithm performs better for warped non-uniform sites, as well as gridiron and fragmented uniform sites. It also produces more similar parcel areas and widths. The Generalized Parcel Divider 1 algorithm performs better for gridiron non-uniform sites. The Straight Skeleton algorithm performs better for loop and lollipop networks as well as fragmented non-uniform and warped uniform sites. It also produces more similar parcel shapes and patterns.

Computer aided design of solonoid magnets

Energy Technology Data Exchange (ETDEWEB)

DeOlivares, J.M.

1978-06-01

Computer programs utilizing Legendre functions and elliptic integral functions have been written to aid in the design of solenoid magnets. The field inside an axisymmetric magnet can be expanded in a converging power series of Legendre functions. The Legendre function approach is very useful for designing solenoid magnets with a high degree of field uniformity. This approach has been programed on the LBL CDC 7600 computer so that one can design an axisymmetric magnet which meets any desired field structure. Two examples of computer designed solenoids are presented. A computer program utilizing elliptic integral functions was also written for the LBL CDC 7600 computer. This method was used in a computer program to verify the results obtained from the Legendre approach and for field calculations within the conductor. The elliptic integral field calculations within the conductor showed that thin solenoids produce field peaking at the ends of the magnet. Computer data is generated for various magnet geometries and compared with theoretical predictions. Computer results and theoretical prediction both show that field peaking is reduced for longer coils, increased for thinner coils and field peaking is a logarithmic function of length, thickness and radius.

Algorithm for counting large directed loops

Energy Technology Data Exchange (ETDEWEB)

Bianconi, Ginestra [Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34014 Trieste (Italy); Gulbahce, Natali [Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, NM 87545 (United States)

2008-06-06

We derive a Belief-Propagation algorithm for counting large loops in a directed network. We evaluate the distribution of the number of small loops in a directed random network with given degree sequence. We apply the algorithm to a few characteristic directed networks of various network sizes and loop structures and compare the algorithm with exhaustive counting results when possible. The algorithm is adequate in estimating loop counts for large directed networks and can be used to compare the loop structure of directed networks and their randomized counterparts.

Hardware modules of the RSA algorithm

Directory of Open Access Journals (Sweden)

Škobić Velibor

2014-01-01

Full Text Available This paper describes basic principles of data protection using the RSA algorithm, as well as algorithms for its calculation. The RSA algorithm is implemented on FPGA integrated circuit EP4CE115F29C7, family Cyclone IV, Altera. Four modules of Montgomery algorithm are designed using VHDL. Synthesis and simulation are done using Quartus II software and ModelSim. The modules are analyzed for different key lengths (16 to 1024 in terms of the number of logic elements, the maximum frequency and speed.

PROPOSAL OF ALGORITHM FOR ROUTE OPTIMIZATION

Directory of Open Access Journals (Sweden)

Robert Ramon de Carvalho Sousa

2016-06-01

Full Text Available This article uses “Six Sigma” methodology for the elaboration of an algorithm for routing problems which is able to obtain more efficient results than those from Clarke and Wright´s (CW algorithm (1964 in situations of random increase of product delivery demands, facing the incapability of service level increase . In some situations, the algorithm proposed obtained more efficient results than the CW algorithm. The key factor was a reduction in the number of mistakes (one way routes and in the level of result variation.

Toward human-centered algorithm design

Directory of Open Access Journals (Sweden)

Eric PS Baumer

2017-07-01

Full Text Available As algorithms pervade numerous facets of daily life, they are incorporated into systems for increasingly diverse purposes. These systems’ results are often interpreted differently by the designers who created them than by the lay persons who interact with them. This paper offers a proposal for human-centered algorithm design, which incorporates human and social interpretations into the design process for algorithmically based systems. It articulates three specific strategies for doing so: theoretical, participatory, and speculative. Drawing on the author’s work designing and deploying multiple related systems, the paper provides a detailed example of using a theoretical approach. It also discusses findings pertinent to participatory and speculative design approaches. The paper addresses both strengths and challenges for each strategy in helping to center the process of designing algorithmically based systems around humans.

Designing algorithms using CAD technologies

Directory of Open Access Journals (Sweden)

Alin IORDACHE

2008-01-01

Full Text Available A representative example of eLearning-platform modular application, ‘Logical diagrams’, is intended to be a useful learning and testing tool for the beginner programmer, but also for the more experienced one. The problem this application is trying to solve concerns young programmers who forget about the fundamentals of this domain, algorithmic. Logical diagrams are a graphic representation of an algorithm, which uses different geometrical figures (parallelograms, rectangles, rhombuses, circles with particular meaning that are called blocks and connected between them to reveal the flow of the algorithm. The role of this application is to help the user build the diagram for the algorithm and then automatically generate the C code and test it.

A new chaotic algorithm for image encryption

International Nuclear Information System (INIS)

Gao Haojiang; Zhang Yisheng; Liang Shuyun; Li Dequn

2006-01-01

Recent researches of image encryption algorithms have been increasingly based on chaotic systems, but the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper presents a new nonlinear chaotic algorithm (NCA) which uses power function and tangent function instead of linear function. Its structural parameters are obtained by experimental analysis. And an image encryption algorithm in a one-time-one-password system is designed. The experimental results demonstrate that the image encryption algorithm based on NCA shows advantages of large key space and high-level security, while maintaining acceptable efficiency. Compared with some general encryption algorithms such as DES, the encryption algorithm is more secure

Learning theory of distributed spectral algorithms

International Nuclear Information System (INIS)

Guo, Zheng-Chu; Lin, Shao-Bo; Zhou, Ding-Xuan

2017-01-01

Spectral algorithms have been widely used and studied in learning theory and inverse problems. This paper is concerned with distributed spectral algorithms, for handling big data, based on a divide-and-conquer approach. We present a learning theory for these distributed kernel-based learning algorithms in a regression framework including nice error bounds and optimal minimax learning rates achieved by means of a novel integral operator approach and a second order decomposition of inverse operators. Our quantitative estimates are given in terms of regularity of the regression function, effective dimension of the reproducing kernel Hilbert space, and qualification of the filter function of the spectral algorithm. They do not need any eigenfunction or noise conditions and are better than the existing results even for the classical family of spectral algorithms. (paper)

Finite lattice extrapolation algorithms

International Nuclear Information System (INIS)

Henkel, M.; Schuetz, G.

1987-08-01

Two algorithms for sequence extrapolation, due to von den Broeck and Schwartz and Bulirsch and Stoer are reviewed and critically compared. Applications to three states and six states quantum chains and to the (2+1)D Ising model show that the algorithm of Bulirsch and Stoer is superior, in particular if only very few finite lattice data are available. (orig.)

Improved core protection calculator system algorithm

International Nuclear Information System (INIS)

Yoon, Tae Young; Park, Young Ho; In, Wang Kee; Bae, Jong Sik; Baeg, Seung Yeob

2009-01-01

Core Protection Calculator System (CPCS) is a digitized core protection system which provides core protection functions based on two reactor core operation parameters, Departure from Nucleate Boiling Ratio (DNBR) and Local Power Density (LPD). It generates a reactor trip signal when the core condition exceeds the DNBR or LPD design limit. It consists of four independent channels which adapted a two out of four trip logic. CPCS algorithm improvement for the newly designed core protection calculator system, RCOPS (Reactor COre Protection System), is described in this paper. New features include the improvement of DNBR algorithm for thermal margin, the addition of pre trip alarm generation for auxiliary trip function, VOPT (Variable Over Power Trip) prevention during RPCS (Reactor Power Cutback System) actuation and the improvement of CEA (Control Element Assembly) signal checking algorithm. To verify the improved CPCS algorithm, CPCS algorithm verification tests, 'Module Test' and 'Unit Test', would be performed on RCOPS single channel facility. It is expected that the improved CPCS algorithm will increase DNBR margin and enhance the plant availability by reducing unnecessary reactor trips

Routing algorithms in networks-on-chip

CERN Document Server

Daneshtalab, Masoud

2014-01-01

This book provides a single-source reference to routing algorithms for Networks-on-Chip (NoCs), as well as in-depth discussions of advanced solutions applied to current and next generation, many core NoC-based Systems-on-Chip (SoCs). After a basic introduction to the NoC design paradigm and architectures, routing algorithms for NoC architectures are presented and discussed at all abstraction levels, from the algorithmic level to actual implementation.  Coverage emphasizes the role played by the routing algorithm and is organized around key problems affecting current and next generation, many-core SoCs. A selection of routing algorithms is included, specifically designed to address key issues faced by designers in the ultra-deep sub-micron (UDSM) era, including performance improvement, power, energy, and thermal issues, fault tolerance and reliability.   ·         Provides a comprehensive overview of routing algorithms for Networks-on-Chip and NoC-based, manycore systems; ·         Describe...

Distribution agnostic structured sparsity recovery algorithms

KAUST Repository

Al-Naffouri, Tareq Y.

2013-05-01

We present an algorithm and its variants for sparse signal recovery from a small number of its measurements in a distribution agnostic manner. The proposed algorithm finds Bayesian estimate of a sparse signal to be recovered and at the same time is indifferent to the actual distribution of its non-zero elements. Termed Support Agnostic Bayesian Matching Pursuit (SABMP), the algorithm also has the capability of refining the estimates of signal and required parameters in the absence of the exact parameter values. The inherent feature of the algorithm of being agnostic to the distribution of the data grants it the flexibility to adapt itself to several related problems. Specifically, we present two important extensions to this algorithm. One extension handles the problem of recovering sparse signals having block structures while the other handles multiple measurement vectors to jointly estimate the related unknown signals. We conduct extensive experiments to show that SABMP and its variants have superior performance to most of the state-of-the-art algorithms and that too at low-computational expense. © 2013 IEEE.

Analysing Music with Point-Set Compression Algorithms

DEFF Research Database (Denmark)

Meredith, David

2016-01-01

Several point-set pattern-discovery and compression algorithms designed for analysing music are reviewed and evaluated. Each algorithm takes as input a point-set representation of a score in which each note is represented as a point in pitch-time space. Each algorithm computes the maximal...... and sections in pieces of classical music. On the first task, the best-performing algorithms achieved success rates of around 84%. In the second task, the best algorithms achieved mean F1 scores of around 0.49, with scores for individual pieces rising as high as 0.71....

Gradient Evolution-based Support Vector Machine Algorithm for Classification

Science.gov (United States)

Zulvia, Ferani E.; Kuo, R. J.

2018-03-01

This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

Stability and chaos of LMSER PCA learning algorithm

International Nuclear Information System (INIS)

Lv Jiancheng; Y, Zhang

2007-01-01

LMSER PCA algorithm is a principal components analysis algorithm. It is used to extract principal components on-line from input data. The algorithm has both stability and chaotic dynamic behavior under some conditions. This paper studies the local stability of the LMSER PCA algorithm via a corresponding deterministic discrete time system. Conditions for local stability are derived. The paper also explores the chaotic behavior of this algorithm. It shows that the LMSER PCA algorithm can produce chaos. Waveform plots, Lyapunov exponents and bifurcation diagrams are presented to illustrate the existence of chaotic behavior of this algorithm

Methods for calculating anisotropic transfer cross sections

International Nuclear Information System (INIS)

Cai, Shaohui; Zhang, Yixin.

1985-01-01

The Legendre moments of the group transfer cross section, which are widely used in the numerical solution of the transport calculation can be efficiently and accurately constructed from low-order (K = 1--2) successive partial range moments. This is convenient for the generation of group constants. In addition, a technique to obtain group-angle correlation transfer cross section without Legendre expansion is presented. (author)

Dose Calculation Accuracy of the Monte Carlo Algorithm for CyberKnife Compared with Other Commercially Available Dose Calculation Algorithms

International Nuclear Information System (INIS)

Sharma, Subhash; Ott, Joseph; Williams, Jamone; Dickow, Danny

2011-01-01

Monte Carlo dose calculation algorithms have the potential for greater accuracy than traditional model-based algorithms. This enhanced accuracy is particularly evident in regions of lateral scatter disequilibrium, which can develop during treatments incorporating small field sizes and low-density tissue. A heterogeneous slab phantom was used to evaluate the accuracy of several commercially available dose calculation algorithms, including Monte Carlo dose calculation for CyberKnife, Analytical Anisotropic Algorithm and Pencil Beam convolution for the Eclipse planning system, and convolution-superposition for the Xio planning system. The phantom accommodated slabs of varying density; comparisons between planned and measured dose distributions were accomplished with radiochromic film. The Monte Carlo algorithm provided the most accurate comparison between planned and measured dose distributions. In each phantom irradiation, the Monte Carlo predictions resulted in gamma analysis comparisons >97%, using acceptance criteria of 3% dose and 3-mm distance to agreement. In general, the gamma analysis comparisons for the other algorithms were <95%. The Monte Carlo dose calculation algorithm for CyberKnife provides more accurate dose distribution calculations in regions of lateral electron disequilibrium than commercially available model-based algorithms. This is primarily because of the ability of Monte Carlo algorithms to implicitly account for tissue heterogeneities, density scaling functions; and/or effective depth correction factors are not required.

Behavioural modelling using the MOESP algorithm, dynamic neural networks and the Bartels-Stewart algorithm

NARCIS (Netherlands)

Schilders, W.H.A.; Meijer, P.B.L.; Ciggaar, E.

2008-01-01

In this paper we discuss the use of the state-space modelling MOESP algorithm to generate precise information about the number of neurons and hidden layers in dynamic neural networks developed for the behavioural modelling of electronic circuits. The Bartels–Stewart algorithm is used to transform

Algorithmic randomness and physical entropy

International Nuclear Information System (INIS)

Zurek, W.H.

1989-01-01

Algorithmic randomness provides a rigorous, entropylike measure of disorder of an individual, microscopic, definite state of a physical system. It is defined by the size (in binary digits) of the shortest message specifying the microstate uniquely up to the assumed resolution. Equivalently, algorithmic randomness can be expressed as the number of bits in the smallest program for a universal computer that can reproduce the state in question (for instance, by plotting it with the assumed accuracy). In contrast to the traditional definitions of entropy, algorithmic randomness can be used to measure disorder without any recourse to probabilities. Algorithmic randomness is typically very difficult to calculate exactly but relatively easy to estimate. In large systems, probabilistic ensemble definitions of entropy (e.g., coarse-grained entropy of Gibbs and Boltzmann's entropy H=lnW, as well as Shannon's information-theoretic entropy) provide accurate estimates of the algorithmic entropy of an individual system or its average value for an ensemble. One is thus able to rederive much of thermodynamics and statistical mechanics in a setting very different from the usual. Physical entropy, I suggest, is a sum of (i) the missing information measured by Shannon's formula and (ii) of the algorithmic information content---algorithmic randomness---present in the available data about the system. This definition of entropy is essential in describing the operation of thermodynamic engines from the viewpoint of information gathering and using systems. These Maxwell demon-type entities are capable of acquiring and processing information and therefore can ''decide'' on the basis of the results of their measurements and computations the best strategy for extracting energy from their surroundings. From their internal point of view the outcome of each measurement is definite

Relative Pose Estimation Algorithm with Gyroscope Sensor

Directory of Open Access Journals (Sweden)

Shanshan Wei

2016-01-01

Full Text Available This paper proposes a novel vision and inertial fusion algorithm S2fM (Simplified Structure from Motion for camera relative pose estimation. Different from current existing algorithms, our algorithm estimates rotation parameter and translation parameter separately. S2fM employs gyroscopes to estimate camera rotation parameter, which is later fused with the image data to estimate camera translation parameter. Our contributions are in two aspects. (1 Under the circumstance that no inertial sensor can estimate accurately enough translation parameter, we propose a translation estimation algorithm by fusing gyroscope sensor and image data. (2 Our S2fM algorithm is efficient and suitable for smart devices. Experimental results validate efficiency of the proposed S2fM algorithm.

The Chandra Source Catalog: Algorithms

Science.gov (United States)

McDowell, Jonathan; Evans, I. N.; Primini, F. A.; Glotfelty, K. J.; McCollough, M. L.; Houck, J. C.; Nowak, M. A.; Karovska, M.; Davis, J. E.; Rots, A. H.; Siemiginowska, A. L.; Hain, R.; Evans, J. D.; Anderson, C. S.; Bonaventura, N. R.; Chen, J. C.; Doe, S. M.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hall, D. M.; Harbo, P. N.; He, X.; Lauer, J.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-09-01

Creation of the Chandra Source Catalog (CSC) required adjustment of existing pipeline processing, adaptation of existing interactive analysis software for automated use, and development of entirely new algorithms. Data calibration was based on the existing pipeline, but more rigorous data cleaning was applied and the latest calibration data products were used. For source detection, a local background map was created including the effects of ACIS source readout streaks. The existing wavelet source detection algorithm was modified and a set of post-processing scripts used to correct the results. To analyse the source properties we ran the SAO Traceray trace code for each source to generate a model point spread function, allowing us to find encircled energy correction factors and estimate source extent. Further algorithms were developed to characterize the spectral, spatial and temporal properties of the sources and to estimate the confidence intervals on count rates and fluxes. Finally, sources detected in multiple observations were matched, and best estimates of their merged properties derived. In this paper we present an overview of the algorithms used, with more detailed treatment of some of the newly developed algorithms presented in companion papers.

Multidimensional Scaling Localization Algorithm in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhang Dongyang

2014-02-01

Full Text Available Due to the localization algorithm in large-scale wireless sensor network exists shortcomings both in positioning accuracy and time complexity compared to traditional localization algorithm, this paper presents a fast multidimensional scaling location algorithm. By positioning algorithm for fast multidimensional scaling, fast mapping initialization, fast mapping and coordinate transform can get schematic coordinates of node, coordinates Initialize of MDS algorithm, an accurate estimate of the node coordinates and using the PRORUSTES to analysis alignment of the coordinate and final position coordinates of nodes etc. There are four steps, and the thesis gives specific implementation steps of the algorithm. Finally, compared with stochastic algorithms and classical MDS algorithm experiment, the thesis takes application of specific examples. Experimental results show that: the proposed localization algorithm has fast multidimensional scaling positioning accuracy in ensuring certain circumstances, but also greatly improves the speed of operation.

Cascade Error Projection: A New Learning Algorithm

Science.gov (United States)

Duong, T. A.; Stubberud, A. R.; Daud, T.; Thakoor, A. P.

1995-01-01

A new neural network architecture and a hardware implementable learning algorithm is proposed. The algorithm, called cascade error projection (CEP), handles lack of precision and circuit noise better than existing algorithms.

Quantum learning algorithms for quantum measurements

Energy Technology Data Exchange (ETDEWEB)

Bisio, Alessandro, E-mail: alessandro.bisio@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); D' Ariano, Giacomo Mauro, E-mail: dariano@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); Perinotti, Paolo, E-mail: paolo.perinotti@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); Sedlak, Michal, E-mail: michal.sedlak@unipv.it [QUIT Group, Dipartimento di Fisica ' A. Volta' and INFN, via Bassi 6, 27100 Pavia (Italy); Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)

2011-09-12

We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information. -- Highlights: → Optimal learning algorithm for von Neumann measurements. → From 2 copies to 1 copy: the optimal strategy is parallel. → From 3 copies to 1 copy: the optimal strategy must be non-parallel.

Quantum learning algorithms for quantum measurements

International Nuclear Information System (INIS)

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Sedlak, Michal

2011-01-01

We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information. -- Highlights: → Optimal learning algorithm for von Neumann measurements. → From 2 copies to 1 copy: the optimal strategy is parallel. → From 3 copies to 1 copy: the optimal strategy must be non-parallel.

A controllable sensor management algorithm capable of learning

Science.gov (United States)

Osadciw, Lisa A.; Veeramacheneni, Kalyan K.

2005-03-01

Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

WDM Multicast Tree Construction Algorithms and Their Comparative Evaluations

Science.gov (United States)

Makabe, Tsutomu; Mikoshi, Taiju; Takenaka, Toyofumi

We propose novel tree construction algorithms for multicast communication in photonic networks. Since multicast communications consume many more link resources than unicast communications, effective algorithms for route selection and wavelength assignment are required. We propose a novel tree construction algorithm, called the Weighted Steiner Tree (WST) algorithm and a variation of the WST algorithm, called the Composite Weighted Steiner Tree (CWST) algorithm. Because these algorithms are based on the Steiner Tree algorithm, link resources among source and destination pairs tend to be commonly used and link utilization ratios are improved. Because of this, these algorithms can accept many more multicast requests than other multicast tree construction algorithms based on the Dijkstra algorithm. However, under certain delay constraints, the blocking characteristics of the proposed Weighted Steiner Tree algorithm deteriorate since some light paths between source and destinations use many hops and cannot satisfy the delay constraint. In order to adapt the approach to the delay-sensitive environments, we have devised the Composite Weighted Steiner Tree algorithm comprising the Weighted Steiner Tree algorithm and the Dijkstra algorithm for use in a delay constrained environment such as an IPTV application. In this paper, we also give the results of simulation experiments which demonstrate the superiority of the proposed Composite Weighted Steiner Tree algorithm compared with the Distributed Minimum Hop Tree (DMHT) algorithm, from the viewpoint of the light-tree request blocking.

Automatic Circuit Design and Optimization Using Modified PSO Algorithm

Directory of Open Access Journals (Sweden)

Subhash Patel

2016-04-01

Full Text Available In this work, we have proposed modified PSO algorithm based optimizer for automatic circuit design. The performance of the modified PSO algorithm is compared with two other evolutionary algorithms namely ABC algorithm and standard PSO algorithm by designing two stage CMOS operational amplifier and bulk driven OTA in 130nm technology. The results show the robustness of the proposed algorithm. With modified PSO algorithm, the average design error for two stage op-amp is only 0.054% in contrast to 3.04% for standard PSO algorithm and 5.45% for ABC algorithm. For bulk driven OTA, average design error is 1.32% with MPSO compared to 4.70% with ABC algorithm and 5.63% with standard PSO algorithm.

An investigation of genetic algorithms

International Nuclear Information System (INIS)

Douglas, S.R.

1995-04-01

Genetic algorithms mimic biological evolution by natural selection in their search for better individuals within a changing population. they can be used as efficient optimizers. This report discusses the developing field of genetic algorithms. It gives a simple example of the search process and introduces the concept of schema. It also discusses modifications to the basic genetic algorithm that result in species and niche formation, in machine learning and artificial evolution of computer programs, and in the streamlining of human-computer interaction. (author). 3 refs., 1 tab., 2 figs

Subcubic Control Flow Analysis Algorithms

DEFF Research Database (Denmark)

Midtgaard, Jan; Van Horn, David

We give the first direct subcubic algorithm for performing control flow analysis of higher-order functional programs. Despite the long held belief that inclusion-based flow analysis could not surpass the ``cubic bottleneck, '' we apply known set compression techniques to obtain an algorithm...... that runs in time O(n^3/log n) on a unit cost random-access memory model machine. Moreover, we refine the initial flow analysis into two more precise analyses incorporating notions of reachability. We give subcubic algorithms for these more precise analyses and relate them to an existing analysis from...

The theory of hybrid stochastic algorithms

International Nuclear Information System (INIS)

Kennedy, A.D.

1989-01-01

These lectures introduce the family of Hybrid Stochastic Algorithms for performing Monte Carlo calculations in Quantum Field Theory. After explaining the basic concepts of Monte Carlo integration we discuss the properties of Markov processes and one particularly useful example of them: the Metropolis algorithm. Building upon this framework we consider the Hybrid and Langevin algorithms from the viewpoint that they are approximate versions of the Hybrid Monte Carlo method; and thus we are led to consider Molecular Dynamics using the Leapfrog algorithm. The lectures conclude by reviewing recent progress in these areas, explaining higher-order integration schemes, the asymptotic large-volume behaviour of the various algorithms, and some simple exact results obtained by applying them to free field theory. It is attempted throughout to give simple yet correct proofs of the various results encountered. 38 refs

A sampling algorithm for segregation analysis

Directory of Open Access Journals (Sweden)

Henshall John

2001-11-01

Full Text Available Abstract Methods for detecting Quantitative Trait Loci (QTL without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC method which samples the pedigree of the whole population jointly is described. Simultaneous sampling of the pedigree was achieved by sampling descent graphs using the Metropolis-Hastings algorithm. A descent graph describes the inheritance state of each allele and provides pedigrees guaranteed to be consistent with Mendelian sampling. Sampling descent graphs overcomes most, if not all, of the limitations incurred by iterative peeling algorithms. The algorithm was able to find the QTL in most of the simulated populations. However, when the QTL was not modeled or found then its effect was ascribed to the polygenic component. No QTL were detected when they were not simulated.

Collective probabilities algorithm for surface hopping calculations

International Nuclear Information System (INIS)

Bastida, Adolfo; Cruz, Carlos; Zuniga, Jose; Requena, Alberto

2003-01-01

General equations that transition probabilities of the hopping algorithms in surface hopping calculations must obey to assure the equality between the average quantum and classical populations are derived. These equations are solved for two particular cases. In the first it is assumed that probabilities are the same for all trajectories and that the number of hops is kept to a minimum. These assumptions specify the collective probabilities (CP) algorithm, for which the transition probabilities depend on the average populations for all trajectories. In the second case, the probabilities for each trajectory are supposed to be completely independent of the results from the other trajectories. There is, then, a unique solution of the general equations assuring that the transition probabilities are equal to the quantum population of the target state, which is referred to as the independent probabilities (IP) algorithm. The fewest switches (FS) algorithm developed by Tully is accordingly understood as an approximate hopping algorithm which takes elements from the accurate CP and IP solutions. A numerical test of all these hopping algorithms is carried out for a one-dimensional two-state problem with two avoiding crossings which shows the accuracy and computational efficiency of the collective probabilities algorithm proposed, the limitations of the FS algorithm and the similarity between the results offered by the IP algorithm and those obtained with the Ehrenfest method

The Research and Application of SURF Algorithm Based on Feature Point Selection Algorithm

Directory of Open Access Journals (Sweden)

Zhang Fang Hu

2014-04-01

Full Text Available As the pixel information of depth image is derived from the distance information, when implementing SURF algorithm with KINECT sensor for static sign language recognition, there can be some mismatched pairs in palm area. This paper proposes a feature point selection algorithm, by filtering the SURF feature points step by step based on the number of feature points within adaptive radius r and the distance between the two points, it not only greatly improves the recognition rate, but also ensures the robustness under the environmental factors, such as skin color, illumination intensity, complex background, angle and scale changes. The experiment results show that the improved SURF algorithm can effectively improve the recognition rate, has a good robustness.

Sorting on STAR. [CDC computer algorithm timing comparison

Science.gov (United States)

Stone, H. S.

1978-01-01

Timing comparisons are given for three sorting algorithms written for the CDC STAR computer. One algorithm is Hoare's (1962) Quicksort, which is the fastest or nearly the fastest sorting algorithm for most computers. A second algorithm is a vector version of Quicksort that takes advantage of the STAR's vector operations. The third algorithm is an adaptation of Batcher's (1968) sorting algorithm, which makes especially good use of vector operations but has a complexity of N(log N)-squared as compared with a complexity of N log N for the Quicksort algorithms. In spite of its worse complexity, Batcher's sorting algorithm is competitive with the serial version of Quicksort for vectors up to the largest that can be treated by STAR. Vector Quicksort outperforms the other two algorithms and is generally preferred. These results indicate that unusual instruction sets can introduce biases in program execution time that counter results predicted by worst-case asymptotic complexity analysis.

Numerical predictions and measurements in the lubrication of aeronautical engine and transmission components

Science.gov (United States)

Moraru, Laurentiu Eugen

2005-11-01

This dissertation treats a variety of aspects of the lubrication of mechanical components encountered in aeronautical engines and transmissions. The study covers dual clearance squeeze film dampers, mixed elastohydrodynamic lubrication (EHL) cases and thermal elastohydrodynamic contacts. The dual clearance squeeze film damper (SFD) invented by Fleming is investigated both theoretically and experimentally for cases when the sleeve that separates the two oil films is free to float and for cases when the separating sleeve is supported by a squirrel cage. The Reynolds equation is developed to handle each of these cases and it is solved analytically for short bearings. A rotordynamic model of a test rig is developed, for both the single and dual SFD cases. A computer code is written to calculate the motion of the test rig rotor. Experiments are performed in order to validate the theoretical results. Rotordynamics computations are found to favorably agree with measured data. A probabilistic model for mixed EHL is developed and implemented. Surface roughness of gears are measured and processed. The mixed EHL model incorporates the average flow model of Patir and Cheng and the elasto-plastic contact mechanics model of Chang Etsion and Bogy. The current algorithm allows for the computation of the load supported by an oil film and for the load supported by the elasto-plastically deformed asperities. This work also presents a way to incorporate the effect of the fluid induced roughness deformation by utilizing the "amplitude reduction" results provided by the deterministic analyses. The Lobatto point Gaussian integration algorithm of Elrod and Brewe was extended for thermal lubrication problems involving compressible lubricants and it was implemented in thermal elastohydrodynamic cases. The unknown variables across the film are written in series of Legendre polynomials. The thermal Reynolds equation is obtained in terms of the series coefficients and it is proven that it can

An algorithm for reduct cardinality minimization

KAUST Repository

AbouEisha, Hassan M.

2013-12-01

This is devoted to the consideration of a new algorithm for reduct cardinality minimization. This algorithm transforms the initial table to a decision table of a special kind, simplify this table, and use a dynamic programming algorithm to finish the construction of an optimal reduct. Results of computer experiments with decision tables from UCI ML Repository are discussed. © 2013 IEEE.

An algorithm for reduct cardinality minimization

KAUST Repository

AbouEisha, Hassan M.; Al Farhan, Mohammed; Chikalov, Igor; Moshkov, Mikhail

2013-01-01

This is devoted to the consideration of a new algorithm for reduct cardinality minimization. This algorithm transforms the initial table to a decision table of a special kind, simplify this table, and use a dynamic programming algorithm to finish the construction of an optimal reduct. Results of computer experiments with decision tables from UCI ML Repository are discussed. © 2013 IEEE.

A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for Distribution Feeder Reconfiguration

International Nuclear Information System (INIS)

Niknam, Taher; Azadfarsani, Ehsan; Jabbari, Masoud

2012-01-01

Highlights: ► Network reconfiguration is a very important way to save the electrical energy. ► This paper proposes a new algorithm to solve the DFR. ► The algorithm combines NFAPSO with NM. ► The proposed algorithm is tested on two distribution test feeders. - Abstract: Network reconfiguration for loss reduction in distribution system is a very important way to save the electrical energy. This paper proposes a new hybrid evolutionary algorithm to solve the Distribution Feeder Reconfiguration problem (DFR). The algorithm is based on combination of a New Fuzzy Adaptive Particle Swarm Optimization (NFAPSO) and Nelder–Mead simplex search method (NM) called NFAPSO–NM. In the proposed algorithm, a new fuzzy adaptive particle swarm optimization includes two parts. The first part is Fuzzy Adaptive Binary Particle Swarm Optimization (FABPSO) that determines the status of tie switches (open or close) and second part is Fuzzy Adaptive Discrete Particle Swarm Optimization (FADPSO) that determines the sectionalizing switch number. In other side, due to the results of binary PSO(BPSO) and discrete PSO(DPSO) algorithms highly depends on the values of their parameters such as the inertia weight and learning factors, a fuzzy system is employed to adaptively adjust the parameters during the search process. Moreover, the Nelder–Mead simplex search method is combined with the NFAPSO algorithm to improve its performance. Finally, the proposed algorithm is tested on two distribution test feeders. The results of simulation show that the proposed method is very powerful and guarantees to obtain the global optimization.

Optimized parallel convolutions for non-linear fluid models of tokamak ηi turbulence

International Nuclear Information System (INIS)

Milovich, J.L.; Tomaschke, G.; Kerbel, G.D.

1993-01-01

Non-linear computational fluid models of plasma turbulence based on spectral methods typically spend a large fraction of the total computing time evaluating convolutions. Usually these convolutions arise from an explicit or semi implicit treatment of the convective non-linearities in the problem. Often the principal convective velocity is perpendicular to magnetic field lines allowing a reduction of the convolution to two dimensions in an appropriate geometry, but beyond this, different models vary widely in the particulars of which mode amplitudes are selectively evolved to get the most efficient representation of the turbulence. As the number of modes in the problem, N, increases, the amount of computation required for this part of the evolution algorithm then scales as N 2 /timestep for a direct or analytic method and N ln N/timestep for a pseudospectral method. The constants of proportionality depend on the particulars of mode selection and determine the size problem for which the method will perform equally. For large enough N, the pseudospectral method performance is always superior, though some problems do not require correspondingly high resolution. Further, the Courant condition for numerical stability requires that the timestep size must decrease proportionately as N increases, thus accentuating the need to have fast methods for larger N problems. The authors have developed a package for the Cray system which performs these convolutions for a rather arbitrary mode selection scheme using either method. The package is highly optimized using a combination of macro and microtasking techniques, as well as vectorization and in some cases assembly coded routines. Parts of the package have also been developed and optimized for the CM200 and CM5 system. Performance comparisons with respect to problem size, parallelization, selection schemes and architecture are presented

Efficient sequential and parallel algorithms for record linkage.

Science.gov (United States)

Mamun, Abdullah-Al; Mi, Tian; Aseltine, Robert; Rajasekaran, Sanguthevar

2014-01-01

Integrating data from multiple sources is a crucial and challenging problem. Even though there exist numerous algorithms for record linkage or deduplication, they suffer from either large time needs or restrictions on the number of datasets that they can integrate. In this paper we report efficient sequential and parallel algorithms for record linkage which handle any number of datasets and outperform previous algorithms. Our algorithms employ hierarchical clustering algorithms as the basis. A key idea that we use is radix sorting on certain attributes to eliminate identical records before any further processing. Another novel idea is to form a graph that links similar records and find the connected components. Our sequential and parallel algorithms have been tested on a real dataset of 1,083,878 records and synthetic datasets ranging in size from 50,000 to 9,000,000 records. Our sequential algorithm runs at least two times faster, for any dataset, than the previous best-known algorithm, the two-phase algorithm using faster computation of the edit distance (TPA (FCED)). The speedups obtained by our parallel algorithm are almost linear. For example, we get a speedup of 7.5 with 8 cores (residing in a single node), 14.1 with 16 cores (residing in two nodes), and 26.4 with 32 cores (residing in four nodes). We have compared the performance of our sequential algorithm with TPA (FCED) and found that our algorithm outperforms the previous one. The accuracy is the same as that of this previous best-known algorithm.

A new algorithm for hip fracture surgery

DEFF Research Database (Denmark)

Palm, Henrik; Krasheninnikoff, Michael; Holck, Kim

2012-01-01

Background and purpose Treatment of hip fracture patients is controversial. We implemented a new operative and supervision algorithm (the Hvidovre algorithm) for surgical treatment of all hip fractures, primarily based on own previously published results. Methods 2,000 consecutive patients over 50...... years of age who were admitted and operated on because of a hip fracture were prospectively included. 1,000 of these patients were included after implementation of the algorithm. Demographic parameters, hospital treatment, and reoperations within the first postoperative year were assessed from patient...... by reoperations was reduced from 24% of total hospitalization before the algorithm was introduced to 18% after it was introduced. Interpretation It is possible to implement an algorithm for treatment of all hip fracture patients in a large teaching hospital. In our case, the Hvidovre algorithm both raised...

Modified BTC Algorithm for Audio Signal Coding

Directory of Open Access Journals (Sweden)

TOMIC, S.

2016-11-01

Full Text Available This paper describes modification of a well-known image coding algorithm, named Block Truncation Coding (BTC and its application in audio signal coding. BTC algorithm was originally designed for black and white image coding. Since black and white images and audio signals have different statistical characteristics, the application of this image coding algorithm to audio signal presents a novelty and a challenge. Several implementation modifications are described in this paper, while the original idea of the algorithm is preserved. The main modifications are performed in the area of signal quantization, by designing more adequate quantizers for audio signal processing. The result is a novel audio coding algorithm, whose performance is presented and analyzed in this research. The performance analysis indicates that this novel algorithm can be successfully applied in audio signal coding.

A divide-and-conquer algorithm for large-scale de novo transcriptome assembly through combining small assemblies from existing algorithms.

Science.gov (United States)

Sze, Sing-Hoi; Parrott, Jonathan J; Tarone, Aaron M

2017-12-06

While the continued development of high-throughput sequencing has facilitated studies of entire transcriptomes in non-model organisms, the incorporation of an increasing amount of RNA-Seq libraries has made de novo transcriptome assembly difficult. Although algorithms that can assemble a large amount of RNA-Seq data are available, they are generally very memory-intensive and can only be used to construct small assemblies. We develop a divide-and-conquer strategy that allows these algorithms to be utilized, by subdividing a large RNA-Seq data set into small libraries. Each individual library is assembled independently by an existing algorithm, and a merging algorithm is developed to combine these assemblies by picking a subset of high quality transcripts to form a large transcriptome. When compared to existing algorithms that return a single assembly directly, this strategy achieves comparable or increased accuracy as memory-efficient algorithms that can be used to process a large amount of RNA-Seq data, and comparable or decreased accuracy as memory-intensive algorithms that can only be used to construct small assemblies. Our divide-and-conquer strategy allows memory-intensive de novo transcriptome assembly algorithms to be utilized to construct large assemblies.

Fractal Landscape Algorithms for Environmental Simulations

Science.gov (United States)

Mao, H.; Moran, S.

2014-12-01

Natural science and geographical research are now able to take advantage of environmental simulations that more accurately test experimental hypotheses, resulting in deeper understanding. Experiments affected by the natural environment can benefit from 3D landscape simulations capable of simulating a variety of terrains and environmental phenomena. Such simulations can employ random terrain generation algorithms that dynamically simulate environments to test specific models against a variety of factors. Through the use of noise functions such as Perlin noise, Simplex noise, and diamond square algorithms, computers can generate simulations that model a variety of landscapes and ecosystems. This study shows how these algorithms work together to create realistic landscapes. By seeding values into the diamond square algorithm, one can control the shape of landscape. Perlin noise and Simplex noise are also used to simulate moisture and temperature. The smooth gradient created by coherent noise allows more realistic landscapes to be simulated. Terrain generation algorithms can be used in environmental studies and physics simulations. Potential studies that would benefit from simulations include the geophysical impact of flash floods or drought on a particular region and regional impacts on low lying area due to global warming and rising sea levels. Furthermore, terrain generation algorithms also serve as aesthetic tools to display landscapes (Google Earth), and simulate planetary landscapes. Hence, it can be used as a tool to assist science education. Algorithms used to generate these natural phenomena provide scientists a different approach in analyzing our world. The random algorithms used in terrain generation not only contribute to the generating the terrains themselves, but are also capable of simulating weather patterns.

Executable Pseudocode for Graph Algorithms

NARCIS (Netherlands)

B. Ó Nualláin (Breanndán)

2015-01-01

textabstract Algorithms are written in pseudocode. However the implementation of an algorithm in a conventional, imperative programming language can often be scattered over hundreds of lines of code thus obscuring its essence. This can lead to difficulties in understanding or verifying the

Algorithms for Decision Tree Construction

KAUST Repository

Chikalov, Igor

2011-01-01

The study of algorithms for decision tree construction was initiated in 1960s. The first algorithms are based on the separation heuristic [13, 31] that at each step tries dividing the set of objects as evenly as possible. Later Garey and Graham [28

A Distributed Spanning Tree Algorithm

DEFF Research Database (Denmark)

Johansen, Karl Erik; Jørgensen, Ulla Lundin; Nielsen, Sven Hauge

We present a distributed algorithm for constructing a spanning tree for connected undirected graphs. Nodes correspond to processors and edges correspond to two-way channels. Each processor has initially a distinct identity and all processors perform the same algorithm. Computation as well...

Cascade Error Projection Learning Algorithm

Science.gov (United States)

Duong, T. A.; Stubberud, A. R.; Daud, T.

1995-01-01

A detailed mathematical analysis is presented for a new learning algorithm termed cascade error projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters.

A quantum causal discovery algorithm

Science.gov (United States)

Giarmatzi, Christina; Costa, Fabio

2018-03-01

Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.

Parallelizing flow-accumulation calculations on graphics processing units—From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

Science.gov (United States)

Qin, Cheng-Zhi; Zhan, Lijun

2012-06-01

As one of the important tasks in digital terrain analysis, the calculation of flow accumulations from gridded digital elevation models (DEMs) usually involves two steps in a real application: (1) using an iterative DEM preprocessing algorithm to remove the depressions and flat areas commonly contained in real DEMs, and (2) using a recursive flow-direction algorithm to calculate the flow accumulation for every cell in the DEM. Because both algorithms are computationally intensive, quick calculation of the flow accumulations from a DEM (especially for a large area) presents a practical challenge to personal computer (PC) users. In recent years, rapid increases in hardware capacity of the graphics processing units (GPUs) provided in modern PCs have made it possible to meet this challenge in a PC environment. Parallel computing on GPUs using a compute-unified-device-architecture (CUDA) programming model has been explored to speed up the execution of the single-flow-direction algorithm (SFD). However, the parallel implementation on a GPU of the multiple-flow-direction (MFD) algorithm, which generally performs better than the SFD algorithm, has not been reported. Moreover, GPU-based parallelization of the DEM preprocessing step in the flow-accumulation calculations has not been addressed. This paper proposes a parallel approach to calculate flow accumulations (including both iterative DEM preprocessing and a recursive MFD algorithm) on a CUDA-compatible GPU. For the parallelization of an MFD algorithm (MFD-md), two different parallelization strategies using a GPU are explored. The first parallelization strategy, which has been used in the existing parallel SFD algorithm on GPU, has the problem of computing redundancy. Therefore, we designed a parallelization strategy based on graph theory. The application results show that the proposed parallel approach to calculate flow accumulations on a GPU performs much faster than either sequential algorithms or other parallel GPU

Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

Science.gov (United States)

Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

2016-01-01

Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.

Randomized Filtering Algorithms

DEFF Research Database (Denmark)

Katriel, Irit; Van Hentenryck, Pascal

2008-01-01

of AllDifferent and is generalization, the Global Cardinality Constraint. The first delayed filtering scheme is a Monte Carlo algorithm: its running time is superior, in the worst case, to that of enforcing are consistency after every domain event, while its filtering effectiveness is analyzed...... in the expected sense. The second scheme is a Las Vegas algorithm using filtering triggers: Its effectiveness is the same as enforcing are consistency after every domain event, while in the expected case it is faster by a factor of m/n, where n and m are, respectively, the number of nodes and edges...

Algorithms and Data Structures (lecture 1)

CERN Multimedia

CERN. Geneva

2018-01-01

Algorithms have existed, in one form or another, for as long as humanity has. During the second half of the 20th century, the field was revolutionised with the introduction of ever faster computers. In these lectures we discuss how algorithms are designed, how to evaluate their speed, and how to identify areas of improvement in existing algorithms. An algorithm consists of more than just a series of instructions; almost as important is the memory structure of the data on which it operates. A part of the lectures will be dedicated to a discussion of the various ways one can store data in memory, and their advantages and disadvantages.

Algorithms and Data Structures (lecture 2)

CERN Multimedia

CERN. Geneva

2018-01-01

Algorithms have existed, in one form or another, for as long as humanity has. During the second half of the 20th century, the field was revolutionised with the introduction of ever faster computers. In these lectures we discuss how algorithms are designed, how to evaluate their speed, and how to identify areas of improvement in existing algorithms. An algorithm consists of more than just a series of instructions; almost as important is the memory structure of the data on which it operates. A part of the lectures will be dedicated to a discussion of the various ways one can store data in memory, and their advantages and disadvantages.

Eigenvalue Decomposition-Based Modified Newton Algorithm

Directory of Open Access Journals (Sweden)

Wen-jun Wang

2013-01-01

Full Text Available When the Hessian matrix is not positive, the Newton direction may not be the descending direction. A new method named eigenvalue decomposition-based modified Newton algorithm is presented, which first takes the eigenvalue decomposition of the Hessian matrix, then replaces the negative eigenvalues with their absolute values, and finally reconstructs the Hessian matrix and modifies the searching direction. The new searching direction is always the descending direction. The convergence of the algorithm is proven and the conclusion on convergence rate is presented qualitatively. Finally, a numerical experiment is given for comparing the convergence domains of the modified algorithm and the classical algorithm.

Euclidean shortest paths exact or approximate algorithms

CERN Document Server

Li, Fajie

2014-01-01

This book reviews algorithms for the exact or approximate solution of shortest-path problems, with a specific focus on a class of algorithms called rubberband algorithms. The coverage includes mathematical proofs for many of the given statements.

Searching Algorithms Implemented on Probabilistic Systolic Arrays

Czech Academy of Sciences Publication Activity Database

Kramosil, Ivan

1996-01-01

Roč. 25, č. 1 (1996), s. 7-45 ISSN 0308-1079 R&D Projects: GA ČR GA201/93/0781 Keywords : searching algorithms * probabilistic algorithms * systolic arrays * parallel algorithms Impact factor: 0.214, year: 1996

(MBO) algorithm in multi-reservoir system optimisation

African Journals Online (AJOL)

A comparative study of marriage in honey bees optimisation (MBO) algorithm in ... A practical application of the marriage in honey bees optimisation (MBO) ... to those of other evolutionary algorithms, such as the genetic algorithm (GA), ant ...

An Implementation of RC4+ Algorithm and Zig-zag Algorithm in a Super Encryption Scheme for Text Security

Science.gov (United States)

Budiman, M. A.; Amalia; Chayanie, N. I.

2018-03-01

Cryptography is the art and science of using mathematical methods to preserve message security. There are two types of cryptography, namely classical and modern cryptography. Nowadays, most people would rather use modern cryptography than classical cryptography because it is harder to break than the classical one. One of classical algorithm is the Zig-zag algorithm that uses the transposition technique: the original message is unreadable unless the person has the key to decrypt the message. To improve the security, the Zig-zag Cipher is combined with RC4+ Cipher which is one of the symmetric key algorithms in the form of stream cipher. The two algorithms are combined to make a super-encryption. By combining these two algorithms, the message will be harder to break by a cryptanalyst. The result showed that complexity of the combined algorithm is θ(n2 ), while the complexity of Zig-zag Cipher and RC4+ Cipher are θ(n2 ) and θ(n), respectively.

Parameter Selection for Ant Colony Algorithm Based on Bacterial Foraging Algorithm

Directory of Open Access Journals (Sweden)

Peng Li

2016-01-01

Full Text Available The optimal performance of the ant colony algorithm (ACA mainly depends on suitable parameters; therefore, parameter selection for ACA is important. We propose a parameter selection method for ACA based on the bacterial foraging algorithm (BFA, considering the effects of coupling between different parameters. Firstly, parameters for ACA are mapped into a multidimensional space, using a chemotactic operator to ensure that each parameter group approaches the optimal value, speeding up the convergence for each parameter set. Secondly, the operation speed for optimizing the entire parameter set is accelerated using a reproduction operator. Finally, the elimination-dispersal operator is used to strengthen the global optimization of the parameters, which avoids falling into a local optimal solution. In order to validate the effectiveness of this method, the results were compared with those using a genetic algorithm (GA and a particle swarm optimization (PSO, and simulations were conducted using different grid maps for robot path planning. The results indicated that parameter selection for ACA based on BFA was the superior method, able to determine the best parameter combination rapidly, accurately, and effectively.

Fitting of two and three variate polynomials from experimental data through the least squares method

International Nuclear Information System (INIS)

Sanchez-Miro, J.J.; Sanz-Martin, J.C.

1994-01-01

Obtaining polynomial fittings from observational data in two and three dimensions is an interesting and practical task. Such an arduous problem suggests the development of an automatic code. The main novelty we provide lies in the generalization of the classical least squares method in three FORTRAN 77 programs usable in any sampling problem. Furthermore, we introduce the orthogonal 2D-Legendre function in the fitting process. These FORTRAN 77 programs are equipped with the options to calculate the approximation quality standard indicators, obviously generalized to two and three dimensions (correlation nonlinear factor, confidence intervals, cuadratic mean error, and so on). The aim of this paper is to rectify the absence of fitting algorithms for more than one independent variable in mathematical libraries

Canonical Least-Squares Monte Carlo Valuation of American Options: Convergence and Empirical Pricing Analysis

Directory of Open Access Journals (Sweden)

Xisheng Yu