a discontinuous galerkin method for two temperature plasmas abstract we develop a formulation for the single fluid two temperature equations for simulating two species compressible non equilibrium plasma flows the divergence free condition of the magnetic field is enforced via the characteristic decomposition of an extended nine wave system the source terms are modified appropriately to improve energy and momentum conservation accuracy a spectral hp element algorithm is employed in the discretization combined with a discontinuous galerkin formulation for the advective and diffusive contributions the formulation is conservative and monotonicity is enforced by appropriately lowering the spectral order around discontinuities a new mhd flux introduced here is the mhd hllc harten lax van leer contact wave flux that preserves monotonicity and resolves contact discontinuities better exponential convergence is demonstrated for a magneto hydrostatic problem two tests are presented using the new mhd hllc flux also the differences between the single temperature and the two temperature models are presented for two dimensional plasma flows around bluff bodies

second order volterra filtering and its application to nonlinear system identification some recent results on the design and implementation of second order volterra filters are presented the second order volterra filter is a nonlinear filter with the filter structure of second order volterra series a simple minimum mean square error solution for the volterra filter is derived based on the assumption that the filter input is gaussian also we propose an iterative factorization technique to design a subclass of the volterra filters which can alleviate the complexity of the filtering operations considerably furthermore an adaptive algorithm for the volterra filter is investigated along with its mean convergence and asymptotic excess mean square error finally the utility of the volterra filter is demonstrated by utilizing it in studies of nonlinear drift oscillations of moored vessels subject to random sea waves

adaptive noise smoothing filter for images with signal dependent noise in this paper we consider the restoration of images with signal dependent noise the filter is noise smoothing and adapts to local changes in image statistics based on a nonstationary mean nonstationary variance nmnv image model for images degraded by a class of uncorrelated signal dependent noise without blur the adaptive noise smoothing filter becomes a point processor and is similar to lee s local statistics algorithm 16 the filter is able to adapt itself to the nonstationary local image statistics in the presence of different types of signal dependent noise for multiplicative noise the adaptive noise smoothing filter is a systematic derivation of lee s algorithm with some extensions that allow different estimators for the local image variance the advantage of the derivation is its easy extension to deal with various types of signal dependent noise film grain and poisson signal dependent restoration problems are also considered as examples all the nonstationary image statistical parameters needed for the filter can be estimated from the noisy image and no a priori information about the original image is required

numerical simulations for radiation hydrodynamics a finite difference scheme is proposed for two dimensional radiation hydrodynamical equations in the transport limit the scheme is of godunov type in which the set of time averaged flux needed in the scheme is calculated through riemann problems solved in the scheme flow signals are explicitly treated while radiation signals are implicitly treated flow fields and radiation fields are updated simultaneously an iterative approach is proposed to solve the set of nonlinear algebraic equations arising from the implicitness of the scheme the sweeping method used in the scheme significantly reduces the number of iterations or computer cpu time needed a new approach to further accelerate the convergence is proposed which further reduces the number of iterations needed by more than one order no matter how many cells radiation signals propagate in one time step only an extremely small number of iterations are needed in the scheme and each iteration costs only about 0 8 percent of computer cpu time which is needed for one time step of a second order accurate and fully explicit scheme two dimensional problems are treated through a dimensionally split technique therefore iterations for solving the set of algebraic equations are carried out only in each one dimensional sweep through numerical examples it is shown that the scheme keeps the principle advantages of godunov schemes for flow motion in the time scale of flow motion numerical results are the same as those obtained from a second order accurate and fully explicit scheme the acceleration of the convergence proposed in this paper may be directly applied to other hyperbolic systems

hopf bifurcation in a leaky faucet experiment in a leaky faucet experiment an inverse hopf bifurcation was observed as one increases the water flux before the occurrence of the continuous flow for values of the drop rate smaller than the critical drop rate the movement is periodic or quasiperiodic with a finite amplitude of the time series at the critical point the amplitude of the time series vanishes and it suggests the bifurcation point as the threshold of the continuous flow c 1995 the american physical society

stochastic and deterministic networks for texture segmentation several texture segmentation algorithms based on deterministic and stochastic relaxation principles and their implementation on parallel networks are described the segmentation process is posed as an optimization problem and two different optimality criteria are considered the first criterion involves maximizing the posterior distribution of the intensity field given the label field maximum a posteriori estimate the posterior distribution of the texture labels is derived by modeling the textures as gauss markov random fields gmrfs and characterizing the distribution of different texture labels by a discrete multilevel markov model a stochastic learning algorithm is proposed this iterated hill climbing algorithm combines fast convergence of deterministic relaxation with the sustained exploration of the stochastic algorithms but is guaranteed to find only a local minimum the second optimality criterion requires minimizing the expected percentage of misclassification per pixel by maximizing the posterior marginal distribution and the maximum posterior marginal algorithm is used to obtain the corresponding solution all these methods implemented on parallel networks can be easily extended for hierarchical segmentation results of the various schemes in classifying some real textured images are presented

image classification using spectral and spatial information based on mrf models a new criterion for classifying multispectral remote sensing images or textured images by using spectral and spatial information is proposed the images are modeled with a hierarchical markov random field mrf model that consists of the observed intensity process and the hidden class label process the class labels are estimated according to the maximum a posteriori map criterion but some reasonable approximations are used to reduce the computational load a stepwise classification algorithm is derived and is confirmed by simulation and experimental results

non uniform convergence of finite volume schemes for riemann problems of ideal magnetohydrodynamics this paper presents riemann test problems for ideal magnetohydrodynamics mhd finite volume schemes the test problems place emphasis on the hyperbolic irregularities of the ideal mhd system namely the occurrence of intermediate shocks and non unique solutions we investigate numerical solutions for the test problems obtained by several commonly used methods roe hlle central scheme all methods turned out to show a non uniform convergence behavior which may be paraphrased as pseudo convergence initially the methods show convergence towards a wrong solution with irregular wave patterns only after heavy grid refinement the methods switch to converge to the true solution this behavior is most pronounced whenever the solution should be unique but its phase space trajectory lies in the vicinity of that of a non unique solution we show detailed grid convergence studies and empirical error analysis the results may be related to similar results for a 2 2 model system and to time dependent investigations of other authors the non uniform convergence is expected to be present for any diffusive finite volume method and question the reliability of coarse grid ideal mhd solutions also in higher space dimensions

a free lagrange augmented godunov method for the simulation of elastic plastic solids a lagrangian finite volume godunov scheme is extended to simulate two dimensional solids in planar geometry the scheme employs an elastic perfectly plastic material model implemented using the method of radial return and either the stiffened gas or osborne equation of state to describe the material the problem of mesh entanglement common to conventional two dimensional lagrangian schemes is avoided by utilising the free lagrange method the lagrangian formulation enables features convecting at the local velocity such as material interfaces to be resolved with minimal numerical dissipation the governing equations are split into separate subproblems and solved sequentially in time using a time operator split procedure local riemann problems are solved using a two shock approximate riemann solver and piecewise linear data reconstruction is employed using a muscl based approach to improve spatial accuracy to illustrate the effectiveness of the technique numerical simulations are presented and compared with results from commercial fixed connectivity lagrangian and smooth particle hydrodynamics solvers autodyn 2d the simulations comprise the low velocity impact of an aluminium projectile on a semi infinite target the collapse of a thick walled beryllium cylinder and the high velocity impact of cylindrical aluminium and steel projectiles on a thin aluminium target the analytical solution for the collapse of a thick walled cylinder is also presented for comparison

a generalized em algorithm for 3 d bayesian reconstruction from poisson data using gibbs priors a generalized expectation maximization gem algorithm is developed for bayesian reconstruction based on locally correlated markov random field priors in the form of gibbs functions and on the poisson data model for the m step of the algorithm a form of coordinate gradient ascent is derived the algorithm reduces to the em maximum likelihood algorithm as the markov random field prior tends towards a uniform distribution three different gibbs function priors are examined reconstructions of 3 d images obtained from the poisson model of single photon emission computed tomography are presented

image sequence filtering in quantum limited noise with applications to low dose fluoroscopy clinical angiography requires hundreds of x ray images putting the patients and particularly the medical staff at risk dosage reduction involves an inevitable sacrifice in image quality in this work the latter problem is addressed by first modeling the signal dependent poisson distributed noise that arises as a result of this dosage reduction the commonly utilized noise model for single images is shown to be obtainable from the new model stochastic temporal filtering techniques are proposed to enhance clinical fluoroscopy sequences corrupted by quantum mottle the temporal versions of these filters as developed here are more suitable for filtering image sequences as correlations along the time axis can be utilized for these dynamic sequences the problem of displacement field estimation is treated in conjunction with the filtering stage to ensure that the temporal correlations are taken along the direction of motion to prevent object blur

long range anticorrelations and non gaussian behavior of the heartbeat we find that the successive increments in the cardiac beat to beat interals of healthy subjects display scale invariant long range anticorrelations up to 10 4 heart beats furthermore we find that the histogram for the heartbeat intervals increments is well described by a l evy stable distribution for a group of subjects with severe heart disease we find that the distribution is unchanged but the long range correlations vanish therefore the different scaling behavior in health and disease must relate to the underlying dynamics of the heartbeat

generalized characteristic analysis and guckenheimer structure abstract we develop a generalized characteristic analysis method using this method we study interactions of elementary waves and construct the riemann solutions for two dimensional scalar conservation laws especially we obtain the necessary and sufficient condition of appearance of guckenheimer structure which is something like mach reflection in gas dynamics

stochastic relaxation gibbs distributions and the bayesian restoration of images we make an analogy between images and statistical mechanics systems pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a lattice like physical system the assignment of an energy function in the physical system determines its gibbs distribution because of the gibbs distribution markov random field mrf equivalence this assignment also determines an mrf image model the energy function is a more convenient and natural mechanism for embodying picture attributes than are the local characteristics of the mrf for a range of degradation mechanisms including blurring nonlinear deformations and multiplicative or additive noise the posterior distribution is an mrf with a structure akin to the image model by the analogy the posterior distribution defines another imaginary physical system gradual temperature reduction in the physical system isolates low energy states annealing or what is the same thing the most probable states under the gibbs distribution the analogous operation under the posterior distribution yields the maximum a posteriori map estimate of the image given the degraded observations the result is a highly parallel relaxation algorithm for map estimation we establish convergence properties of the algorithm and we experiment with some simple pictures for which good restorations are obtained at low signal to noise ratios

symbolic dynamics analysis in the dripping faucet experiment abstract we applied symbolic dynamics analysis to data from the dripping faucet experiment three chaotic attractors at different drop rates were analyzed as well as an intermittent behavior by the graphs construction which are approximation to minimal machines we also propose a new graph representation of symbolic sequences whose pattern reflects the set complexity associated to the experimental attractors

inferring statistical complexity in the dripping faucet experiment abstract we have used topological e machine reconstruction to calculate statistical complexity associated to period five orbits in the dripping faucet experiment basic structures related to the periodic movement and to peripheral tracks in the corresponding directed graphs were identified

an implicit scheme for nonideal magnetohydrodynamics a new implicit algorithm is developed for solving the time dependent nonideal magnetohydrodynamic equations it can also be used as an efficient relaxation scheme for steady state solutions the algorithm is a finite volume scheme that uses an approximate riemann solver for the hyperbolic fluxes and central differencing applied on nested control volumes for the parabolic fluxes that arise from the non ideal terms i e resistivity and viscosity in one dimension the scheme is second order accurate in space and time in two or three dimensions the accuracy is between first and second order for the class of problems considered the implicit formulation is stable for any size time step thus allowing efficient tracking of slower transients the implicit operator is inverted using a lower upper symmetric gauss seidel iteration results from several test cases are presented that show good agreement with analytical solutions and illustrate the advantages of the scheme

structure of riemann solutions for 2 dimensional scalar conservation laws abstract we study the structure of riemann solutions for 2 dimensional scalar conservation laws the riemann data are three constants in three fan domains forming different angles we study the dependence of the structure of the solution upon the value of the constants as well as the angles

long range anticorrelations and non gaussian behavior of a leaky faucet we find that intervals between successive drops from a leaky faucet display scale invariant long range anticorrelations characterized by the same exponents of heart beat to beat intervals of healthy subjects this behavior is also confirmed by numerical simulations on lattice and it is faucet width and flow rate independent the histogram for the drop intervals is also well described by a levy distribution with the same index for both histograms of healthy and diseased subjects this additional result corroborates the evidence for similarities between leaky faucets and healthy hearts underlying dynamics

symbol statistics and spatio temporal systems abstract we consider the problem of estimating parameters from time series observations of spatio temporal systems two types of models are considered a a one dimensional coupled map lattice with nearest neighbor diffusive coupling and b the complex ginzburg landau equation in one and two spatial dimensions model parameters are to be estimated using time series observations from only a few sites a symbolic partition of the time series is introduced and the probabilities of observing various symbol sequences in the data are measured the parameter fitting is accomplished by adjusting parameters of the model until it produces time series whose symbol sequences have the same probabilities as the data we show that it is possible to reliably estimate the parameters from a single time series when the spatio temporal dynamics is turbulent i e it displays a wide range of space and time scales with no discernible patterns

asymptotically optimal estimation of ma and arma parameters of non gaussian processes from high order moments a description is given of an asymptotically minimum variance algorithm for estimating the ma moving average and arma autoregressive moving average parameters of non gaussian processes from sample high order moments the algorithm uses the statistical properties covariances and cross covariances of the sample moments explicitly a simpler alternative algorithm that requires only linear operations is also presented the latter algorithm is asymptotically minimum variance in the class of weighted least squares algorithms

image detection under low level illumination image detection under low light level conditions is treated as a hypothesis testing problem in which the observations are modeled as a shot noise process since computing the likelihood ratio for shot noise processes is not feasible the use of a one dimensional test statistic obtained by filtering and sampling the observations is proposed the filter is chosen to maximize a generalized signal to noise ratio the likelihood ratio for the one dimensional test statistic is evaluated numerically by inverting the corresponding characteristic function under each hypothesis

on the statistical analysis of dirty pictures may 7th 1986 professor a f m smith in the chair summary a continuous two dimensional region is partitioned into a fine rectangular array of sites or pixels each pixel having a particular colour belonging to a prescribed finite set the true colouring of the region is unknown but associated with each pixel there is a possibly multivariate record which conveys imperfect information about its colour according to a known statistical model the aim is to reconstruct the true scene with the additional knowledge that pixels close together tend to have the same or similar colours in this paper it is assumed that the local characteristics of the true scene can be represented by a nondegenerate markov random field such information can be combined with the records by bayes theorem and the true scene can be estimated according to standard criteria however the computational burden is enormous and the reconstruction may reflect undesirable largescale properties of the random field thus a simple iterative method of reconstruction is proposed which does not depend on these large scale characteristics the method is illustrated by computer simulations in which the original scene is not directly related to the assumed random field some complications including parameter estimation are discussed potential applications are mentioned briefly

optimal linear quadratic systems for detection and estimation the problem of linear quadratic systems for detection has long been solved by assuming the deflection criterion and gaussian noise it is shown here that the gaussian assumption can be removed and a complete solution is presented for an arbitrary probability distribution with finite fourth order moments the optimal solution can always be obtained by solving a linear system of equations some properties of the optimal systems are developed for particular examples of nongaussian noise it is shown that there is a strong relationship between linear quadratic optimal detection and optimal estimation which extends results known for the purely linear case

derivative riemann solvers for systems of conservation laws and ader methods in this paper we first briefly review the semi analytical method e f toro v a titarev solution of the generalized riemann problem for advection reaction equations proc roy soc london 458 2018 2002 271 281 for solving the derivative riemann problem for systems of hyperbolic conservation laws with source terms next we generalize it to hyperbolic systems for which the riemann problem solution is not available as an application example we implement the new derivative riemann solver in the high order finite volume ader advection schemes we provide numerical examples for the compressible euler equations in two space dimensions which illustrate robustness and high accuracy of the resulting schemes

maximum likelihood estimation of liner signal parameters for poisson processes the estimation of linear signal parameters is studied under the hypothesis of independently poisson distributed measurements a simple interactive maximum likelihood estimator mle is derived and is optimized for rapid convergence it is shown to be statistically optimal in the sense of providing unbiased and minimum variance estimates experimental conditions are identified where mle results in significant performance improvement when compared to conventional linear least squares lls

an iterative riemann solver for systems of hyperbolic conservation laws with application to hyperelastic solid mechanics in this paper we present a general iterative method for the solution of the riemann problem for hyperbolic systems of pdes the method is based on the multiple shooting method for free boundary value problems we demonstrate the method by solving one dimensional riemann problems for hyperelastic solid mechanics even for conditions representative of routine laboratory conditions and military ballistics dramatic differences are seen between the exact and approximate riemann solution the greatest discrepancy arises from misallocation of energy between compressional and thermal modes by the approximate solver resulting in nonphysical entropy and temperature estimates several pathological conditions arise in common practice and modifications to the method to handle these are discussed these include points where genuine nonlinearity is lost degeneracies and eigenvector deficiencies that occur upon melting

a simple riemann solver and high order godunov schemes for hyperbolic systems of conservation laws a simple approximate riemann solver for hyperbolic systems of conservation laws is developed for its use in godunov schemes the solver is based on characteristic formulations and is illustrated through euler and ideal magnetohydrodynamical mhd equations the procedure of a high order godunov scheme incorporated with the riemann solver for one dimensional hyperbolic systems of conservation laws is described in detail the correctness of the scheme is shown by comparison with the piecewise parabolic method for euler equations and by comparison with exact solutions of riemann problems for ideal mhd equations the robustness of the scheme is demonstrated through numerical examples involving more than one strong shock at the same time it is shown that the scheme offers the principle advantages of godunov schemes robust operation in the presence of strong waves thin shock fronts thin contact and slip surface discontinuities

solution of the riemann problem for irreversibly compressible media the riemann problem for an irreversibly compressible medium has been solved this solution introduces the maximum medium density that is attained in the process of active loading to close the system of equations an extra equation is required to describe the transfer of this parameter through the eulerian mesh the possible wave configurations have been analyzed and the corresponding equations for the evaluation of the contact pressure and velocity have been obtained the existence and uniqueness of the solution have been proven the technique of the riemann problem s solution for the arbitrary lagrange euler mesh was developed examples of the riemann problem solution for various wave configurations show that neglecting the bulk elastic plastic deformations yields significant errors in the results both quantitatively and qualitatively copyright 2009 john wiley sons ltd

a second order iterative implicit explicit hybrid scheme for hyperbolic systems of conservation laws an iterative implicit explicit hybrid scheme is proposed for hyperbolic systems of conservation laws each wave in a system may be implicitly or explicitly or partially implicitly and partially explicitly treated depending on its associated courant number in each numerical cell and the scheme is able to smoothly switch between implicit and explicit calculations the scheme is of godunov type in both explicit and implicit regimes is in a strict conservation form and is accurate to second order in both space and time for all courant numbers the computer code for the scheme is easy to vectorize multicolors proposed in this paper may reduce the number of iterations required to reach a converged solution by several orders for a large time step the feature of the scheme is shown through numerical examples