oscillation theorems for differential equations with a nonlinear damping term in this paper we are concerned with a class of nonlinear second order differential equations with a nonlinear damping term passage to more general class of equations allows us to remove a restrictive condition usually imposed on the nonlinearity and as a consequence our results apply to wider classes of nonlinear differential equations two illustrative examples are considered

on oscillation of nonlinear second order differential equation with damping term we present new oscillation criteria for the second order nonlinear differential equation with damping our theorems are stated in general form they complement and extend related results known in the literature the relevance of our results is illustrated with a number of examples to facilitate computations in these examples we use mathematica r a symbolic computer language

oscillation analysis of numerical solutions for nonlinear delay differential equations of hematopoiesis with unimodal production rate this paper is concerned with oscillation and non oscillation of numerical solutions for nonlinear delay differential equation of hematopoiesis with unimodal production rate by investigating the roots of characteristic equation some conditions under which the numerical solution is oscillatory and non oscillatory are obtained the properties of non oscillatory numerical solutions are investigated to verify our results we give numerical experiments

oscillation results for a second order damped differential equation with nonmonotonous nonlinearity abstract we present new oscillation criteria for a nonlinear second order differential equation with a damping term an essential feature of our results is that we do not require the nonlinearity to be nondecreasing furthermore as opposed to the recent results by s r grace 1989 math nachr 141 117 127 1992 j math anal appl 171 220 241 and s r grace and b s lalli 1990 j math anal appl 149 277 311 we do not impose any additional condition on the damping term p t consequently our theorems apply to new classes of equations which are not covered by the known criteria the relevance of the results obtained is illustrated with a number of carefully selected examples

a genetic algorithm approach to the spectral estimation of time series with noise and missed observations this study considers the problem of estimating the autoregressive moving average arma power spectral density when measurements are corrupted by noise and by missed observations the missed observations model is based on a probabilistic structure unlike conventional cases of missed observation in parameter estimation problems the variance of noise is unavailable that is the time points of missed observations are unknown and the probability of missing data needs to be estimated in this situation spectral estimation is more difficult to solve and becomes a highly nonlinear optimization problem with many local minima in this paper we use the genetic algorithm ga method to achieve a global optimal solution with a fast convergence rate for this spectral estimation problem from the simulation results we have determined that the performance is significantly improved if the probability of data loss is considered in the spectral estimation problem

on the oscillation of certain functional differential equations via comparison methods abstract several new criteria for the oscillation of the functional differential equations of the form d dt 1 a n 1 t d dt 1 a n 2 t d dt 1 a 1 t d dt x t q t f x g t 0 are established in this paper

analytic network process for pattern classification problems using genetic algorithms the analytic network process anp is a useful technique for multi attribute decision analysis mcda that employs a network representation to describe interrelationships between diverse attributes owing to effectiveness of the anp in allowing for complex interrelationships between attributes this paper develops an anp based classifier for pattern classification problems with interdependence or independence among attributes to deal with interdependence this study employs genetic algorithms gas to automatically determine elements in the supermatrix that are not easily user specified to find degrees of importance of respective attributes then with the relative importance for each attribute in the limiting supermatrix the current work determines the class label of a pattern by its synthetic evaluation experimental results obtained by the proposed anp based classifier are comparable to those obtained by other fuzzy or non fuzzy classification methods

iga based point cloud fitting using b spline surfaces for reverse engineering reverse engineering is a viable method to create a 3d virtual model of real physical parts usually reverse engineering consists of two main steps 1 measure the object and 2 reconstruct it as a 3d model the measured data are usually represented as a point cloud without topological information and must therefore often be converted into a tensor product b spline surface format which has become an industry standard in computer graphics and in cad systems in this paper a new immune genetic algorithm iga for point cloud fitting that fits a noisy 3d point cloud using a b spline surface with approximate g1 continuity is presented the point cloud is first segmented into a set of quadrilateral patches for every patch a b spline surface is reconstructed using a least squares approximation method and then the surface is optimized to increase the approximation precision using an iga based knots adjustment algorithm finally the b spline patches are stitched together with approximate g1 continuity with a numerical method and the particle swarm optimization pso algorithm a set of experimental results shows that the proposed method achieves better approximation accuracy than the bezier based method and the ga based method

gravitation based classification classification is one of the key issues in the fields of decision sciences and knowledge discovery in this paper we present a new classification method based on gravitational potential energy between particles the basic principle of gravitation based classification gbc algorithm is to find the equilibrium condition of the classifier which is modeled as a classifier line between two groups of fixed particles in the proposed approach the input data is a collection of masses which interact with each other based on newton s universal law of gravitation and the laws of motion we present a convex formulation for this problem that always converges to a global optimum solution the proposed method has been compared with some well known classification approaches and the results confirm the high performance of the proposed method

oscillation criteria for nonlinear differential equations with damping oscillation criteria are established for the nonlinear second order damped differential equation rx px qf x 0 which are different from most known results

some convergence results for howard s algorithm this paper deals with convergence results of howard s algorithm for the resolution of min a in mathcal a b a x c a 0 where b a is a matrix c a is a vector and mathcal a is a compact set we show a global superlinear convergence result under a monotonicity assumption on the matrices b a extensions of howard s algorithm for a max min problem of the form max b in mathcal b min a in mathcal a b a b x c a b 0 are also proposed in the particular case of an obstacle problem of the form min ax b x g 0 where a is an n times n matrix satisfying a monotonicity assumption we show the convergence of howard s algorithm in no more than n iterations instead of the usual 2 n bound still in the case of an obstacle problem we establish the equivalence between howard s algorithm and a primal dual active set algorithm m hintermuller k ito and k kunisch siam j optim 13 2002 pp 865 888 the algorithms are illustrated on the discretization of nonlinear pdes arising in the context of mathematical finance american option and merton s portfolio problem of front propagation problems and for the double obstacle problem

oscillation theorems for certain functional differential equations abstract some new criteria for the oscillation of functional differential equations with a middle term of the form x n t p t x n 1 t h h t x g t are presented

particle swarm optimization for non uniform rational b spline surface reconstruction from clouds of 3d data points this work investigates the use of particle swarm optimization pso to recover the shape of a surface from clouds of either organized or scattered noisy 3d data points a challenging problem that appears recurrently in a wide range of applications such as cad design data visualization virtual reality medical imaging and movie industries in this paper we apply a pso approach in order to reconstruct a non uniform rational b spline nurbs surface of a certain order from a given set of 3d data points in this case surface reconstruction consists of two main tasks 1 surface parameterization and 2 surface fitting both tasks are critical but also troublesome leading to a high dimensional non linear optimization problem our method allows us to obtain all relevant surface data i e parametric values of data points knot vectors control points and their weights in a shot and no pre post processing is required furthermore it yields very good results even in presence of problematic features such as multi branches high genus or self intersections seven examples including open semiclosed closed zero genus high genus surfaces and real world scanned objects described in free form parametric and implicit forms illustrate the good performance of our approach and its superiority over previous approaches in terms of accuracy and generality

a genetic algorithm approach to determine the sample size for attribute control charts determining the sample size for control charts ccs is generally an important problem in the literature in this paper kaya and engin s i kaya o engin a new approach to define sample size at attributes control chart in multistage processes an application in engine piston manufacturing process journal of materials processing technology 183 2007 38 48 model based on minimum cost and maximum acceptance probability to determine the sample size for attribute control charts accs and solved by genetic algorithms gas with linear binary representation structure is handled to solve it by a linear real valued representation a new chromosome structure is also suggested to increase the efficiency of gas the performance of gas depends on mutation and crossover operators and their ratios to determine the most appropriate operators five different mutation and crossover operators are used and they are compared with each other an application in a motor engine factory is illustrated u control charts are constructed with respect to the sample size determined by ga in the model the piston production stages in this factory are monitorized using the obtained control charts

oscillatory and asymptotic behavior of delay differential equations with a nonlinear damping term in this paper we study the oscillatory and asymptotic behavior of the solutions of delay differential equations of the form x n t f t x t x t 0 n even by comparing with certain differential equations of the same or lower order whose behavior is known the obtained criteria can be applied to the delay differential equation x n t q t x t x t sign x t 0 n even where and are positive constants

kamenev type oscillation criteria for even order neutral differential equations with deviating arguments abstract sufficient conditions are established for the oscillation of even order neutral differential equations of the form x t i 1 m p i t x i t n j 1 l q j t f j x j t 0 t t 0 where n 2 is even integer

new kamenev type oscillation criteria for second order nonlinear differential equations with damping abstract some new oscillation criteria are established for the nonlinear damped differential equation r t y p t y q t f y 0 that are different from most known ones in the sense that they are based on a class of new functions t s r defined in the sequel our results are sharper than some previous results which can be seen by the examples at the end of this paper

on oscillation of nonlinear second order differential equations with damping term the paper is concerned with oscillation of a novel class of nonlinear differential equations with a damping term first it is demonstrated how known oscillation results for another intensively studied class of equations can be translated to the one in question and vice versa advantages and drawbacks of such translation are carefully examined then an oscillation criterion for the new class of equations is established the principal result of the paper is compared to those reported in the literature and an illustrative example to which known oscillation criteria fail to apply is provided

path planning on a cuboid using genetic algorithms the traveling salesman problem tsp is one of the most extensively studied problems in the fields of combinatorial optimization and global search heuristics a variety of heuristic algorithms are available for solving euclidean tsp and planar tsps however optimization on a cuboid has potential applications for areas like path planning on the faces of buildings rooms furniture books and products or simulating the behaviors of insects in this paper we address a variant of the tsp in which all points cities and paths solution are on the faces of a cuboid we develop an effective hybrid method based on genetic algorithms and 2 opt to adapt the euclidean tsp to the surface of a cuboid the method was tested on some benchmark problems from tsplib with satisfactory results a web based interactive visualization tool has also been developed using java 3d and optimization results for different point densities on the cuboid are presented

oscillation criteria for second order neutral equations with distributed deviating argument abstract we present new oscillation criteria for the second order neutral delay differential equations with distributed deviating argument r t x t z t a b p t f x g t d 0 t t 0 where z t x t q t x t new oscillation criteria are established which are based on a class of new functions t s l defined in the sequel our results are sharper than some previous results which can be seen by the example at the end of this paper

oscillation behavior of higher order neutral differential equations in this paper we establish sufficient conditions for the oscillation behavior of solutions of nth order neutral functional differential equations with distributed deviating arguments

gp coach genetic programming based learning of compact and accurate fuzzy rule based classification systems for high dimensional problems in this paper we propose gp coach a genetic programming based method for the learning of compact and accurate fuzzy rule based classification systems for high dimensional problems gp coach learns disjunctive normal form rules generated by means of a context free grammar coded as one rule per tree the population constitutes the rule base so it is a genetic cooperative competitive learning approach gp coach uses a token competition mechanism to maintain the diversity of the population and this obliges the rules to compete and cooperate among themselves and allows the obtaining of a compact set of fuzzy rules the results obtained have been validated by the use of non parametric statistical tests showing a good performance in terms of accuracy and interpretability

some oscillation criteria for a class of second order nonlinear damped differential equations a class of second order nonlinear damped differential equations is studied and several new oscillation conditions are obtained our results extend improve and unify a number of existing results and handle the cases which are not covered by known criteria

on three dimensional surface reconstruction methods a survey is presented of some of the surface reconstruction methods that can be found in the literature the focus is on a small recent and important subset of the published reconstruction techniques the techniques are classified based on the surface representation used implicit versus explicit functions a study is made of the important aspects of the surface reconstruction techniques one aspect is the viewpoint invariance of the methods this is an important property if object recognition is the ultimate objective the robustness of the various methods is examined it is determined whether the parameter estimates are biased and the sensitivity to obscuration is addressed the latter two aspects are particularly important for fitting functions in the implicit form a detailed description is given of a parametric reconstruction method for three dimensional object surfaces that involves numeric grid generation techniques and variational principle formulations this technique is invariant to rigid motion in dimensional space

a patchy dynamic programming scheme for a class of hamilton jacobi bellman equations in this paper we present a new algorithm for the solution of hamilton jacobi bellman equations related to optimal control problems the key idea is to divide the domain of computation into subdomains which are shaped by the optimal dynamics of the underlying control problem this can result in a rather complex geometrical subdivision but it has the advantage that every subdomain is invariant with respect to the optimal dynamics and then the solution can be computed independently in each subdomain the features of this dynamics dependent domain decomposition can be exploited to speed up the computation and for an efficient parallelization since the classical transmission conditions at the boundaries of the subdomains can be avoided for their properties the subdomains are patches in the sense introduced by ancona and bressan esaim control optim calc var 4 1999 pp 445 471 several examples in two and three dimensions illustrate the properties of the new method

oscillation criteria for certain nth order differential equations with deviating arguments abstract oscillation criteria for nth order differential equations with deviating arguments of the form x n 1 t 1 x n 1 t f t x g t 0 n even are established where g c t0 r f c t0 r r and 0 is a constant

asymptotics and oscillation of nth order nonlinear dynamic equations on time scales this paper is concerned with nth order nonlinear dynamic equations on time scales of the form r t x n 1 t i 0 k q i t i x i t 0 with n 2 by discussing the signs of ith order derivatives of eventually positive solutions for i 1 n 1 and using the generalized riccati technique and integral averaging technique we derive new criteria for oscillation and asymptotic behavior of the equation our results extend many existing results in the literature

oscillation theorems for nonlinear differential equations of second order abstract in this paper we present some new criteria for the oscillation of the differential equation a t x t x t p t x t q t f x t 0 the obtained results extend improve and correlate a number of existing criteria

integral averaging technique and oscillation of certain even order delay differential equations abstract using the generalized riccati technique and the averaging technique new oscillation criteria for certain even order delay differential equation of the form x n 1 t 1 x n 1 t f t x g t 0 n even are established where g c t0 r f c t0 r r and 0 is a constant

oscillation of even order half linear functional differential equations with damping in this paper a class of even order half linear functional differential equations with damping are studied by using the generalized riccati transformation and the integral averaging technique the new oscillation criteria which generalize and improve some known results are obtained for all solutions of the equations

oscillation criteria for second order nonlinear neutral differential equations by refining the standard integral averaging technique we obtain new oscillation criteria for a class of second order nonlinear neutral differential equations of the form r t x t p t x email protected q t f x t x s t 0 assumptions in our theorems are less restrictive whereas the proofs are significantly simpler compared to those in the recent paper by shi and wang 18 and related contributions to the subject examples are provided to illustrate the relevance of new theorems

interval oscillation criteria for second order nonlinear differential equations with damping new oscillation criteria are established for the nonlinear damped differential equation ry py qf y 0 that are different from most known ones in the sense that they are based on the information only on a sequence of subintervals of t0 rather than on the whole half line our results are sharper than some previous results and extend and improve the recent interval criteria of kong and huang and can be applied to extreme cases such as t0 q s ds in particular several examples that dwell upon the sharp conditions of our results are also included

oscillation theorems for superlinear second order damped differential equations abstract in this paper we concerned with the oscillation of the second order superlinear differential equation of the form a t y t p t y t q t f y t 0 several new oscillation criteria are established under quite general assumptions our methodology is somewhat different from that of previous authors ch g philos oscillation theorems for linear differential equations of second order arch math basel 53 1989 482 492 ch g philos oscillation criteria for second order superlinear differential equations canad j math anal xli 1989 321 340 ch g philos i k purnaras oscillations in superlinear differential equations of second order j math anal appl 165 1992 1 11 y h yu oscillation criteria for second order nonlinear differential equations with damping acta math appl 16 1993 433 441 in chinese our results generalize and extend some earlier results of yu 1993 example is also given to illustrate the results

note on wong s paper using the method of interval integral average we establish some new oscillation criteria which improve the oscillation criteria due to james s w wong

oscillation criteria for second order nonlinear perturbed differential equations abstract we present new oscillation criteria for the second order nonlinear perturbed differential equations these criteria are of a high degree of generality and they extend and unify a number of existing results

oscillation analysis of advertising capital model analytical and numerical studies abstract this paper mainly deals with the oscillation of nonlinear delay differential equation which is used to describe advertising capital model analytically and numerically firstly the condition of oscillation of the analytic solution is presented by the technique of the theory of characteristic secondly the asymptotic behavior of non oscillatory analytic solution is verified thirdly the methods are applied to the mentioned equation some conditions under which the numerical solution oscillates are obtained moreover it is proved that every non oscillatory numerical solution tends to the steady state of the model finally some numerical simulations for verifying the theoretical findings are provided

primal dual extragradient methods for nonlinear nonsmooth pde constrained optimization we study the extension of the chambolle pock primal dual algorithm to nonsmooth optimization problems involving nonlinear operators between function spaces local convergence is shown under technical conditions including metric regularity of the corresponding primal dual optimality conditions we also show convergence for a nesterov type accelerated variant provided one part of the functional is strongly convex we show the applicability of the accelerated algorithm to examples of inverse problems with l 1 and l infty fitting terms as well as of state constrained optimal control problems where convergence can be guaranteed after introducing an arbitrarily small still nonsmooth moreau yosida regularization this is verified in numerical examples

oscillation theorems for second order nonlinear neutral differential equations the purpose of this paper is to study the oscillation of the second order neutral differential equations of the form a t z t c q t x b s t 0 where z t x t p t x t t we explore properties of given equations by examining those of associated first order delay equations new comparison theorems essentially simplify the examination of the equations studied as they allow us to deduce the oscillation of the second order delay differential equation by applying the oscillation criteria obtained to the first order delay equations the results obtained are easy to verify

oscillation criteria for second order nonlinear differential equations with damping abstract for a second order nonlinear differential equation with a damping term we obtain new oscillation criteria without an assumption that has been required for related results reported in the literature over the last two decades two approaches refining the standard integral averaging technique suggested in the paper can be used to derive a variety of simpler oscillation theorems for different classes of nonlinear differential equations and both sets of oscillation criteria established in the paper are of independent interest several examples are provided to illustrate the relevance of the new theorems

multiple shooting with dichotomically stable formulae for linear boundary value problems abstract this paper describes an improvement of england and mattheij s code mutssym for solving linear boundary value problems for ordinary differential equations with may or not give rise to sharp boundary layers the method is based on multiple shooting with a decoupling strategy allowing the calculation of stable solutions according to the increasing or decreasing fundamental modes the integration of the associated initial value problems is performed using a 4 th order symmetric implicit runge kutta method with the dichotomic stability property if the problem is well conditioned the method calculates discrete decaying growing modes controlled by initial terminal conditions corresponding to similar continuous modes a special step size control strategy permits efficient calculation of the numerical solution throughout the interval 1999 elsevier science ltd all rights reserved

ordered upwind methods for static hamilton jacobi equations theory and algorithms we develop a family of fast methods for approximating the solutions to a wide class of static hamilton jacobi pdes these fast methods include both semi lagrangian and fully eulerian versions numerical solutions to these problems are typically obtained by solving large systems of coupled nonlinear discretized equations our techniques which we refer to as ordered upwind methods oums use partial information about the characteristic directions to decouple these nonlinear systems greatly reducing the computational labor our techniques are considered in the context of control theoretic and front propagation problems we begin by discussing existing oums focusing on those designed for isotropic problems we then introduce a new class of oums which decouple systems for general anisotropic problems we prove convergence of one such scheme to the viscosity solution of the corresponding hamilton jacobi pde next we introduce a set of finite differences methods based on an analysis of the role played by anisotropy in the context of front propagation and optimal trajectory problems the performance of the methods is analyzed and computational experiments are performed using test problems from computational geometry and seismology

self organizing genetic algorithm based tuning of pid controllers this paper proposes a self organizing genetic algorithm soga with good global search properties and a high convergence speed first we introduce a new dominant selection operator that enhances the action of the dominant individuals along with a cyclical mutation operator that periodically varies the mutation probability in accordance with evolution generation found in biological evolutionary processes next the soga is constructed using the two operators mentioned above the results of a nonlinear regression analysis demonstrate that the self organizing genetic algorithm is able to avoid premature convergence with a higher convergence speed and also indicate that it possesses self organization properties finally the new algorithm is used to optimize proportional integral derivative pid controller parameters our simulation results indicate that a suitable set of pid parameters can be calculated by the proposed soga

oscillation behavior of even order nonlinear neutral differential equations with variable coefficients in this paper some sufficient conditions are obtained for the oscillation of all solutions of even order nonlinear neutral differential equations with variable coefficients our results improve and generalize known results in particular the results are new even when n 2

non oscillatory solutions for a nonlinear neutral delay differential equation abstract we study the existence of non oscillatory bounded solutions for a second order nonlinear neutral delay differential equation some sufficient conditions for the existence of non oscillatory bounded solutions with positive lower bound or negative upper bound are established and the non oscillatory solutions with decay as t are discussed

fast semi lagrangian schemes for the eikonal equation and applications we introduce and analyze a fast version of the semi lagrangian algorithm for front propagation originally proposed in m falcone the minimum time problem and its applications to front propagation in motion by mean curvature and related topics a visintin and g buttazzo eds de gruyter berlin 1994 pp 70 88 the new algorithm is obtained using the local definition of the approximate solution typical of semi lagrangian schemes and redefining the set of neighboring nodes necessary for fast marching schemes a new proof of convergence is needed since that definition produces a new narrow band centered at the interphase which is larger than the one used in fast marching methods based on finite differences we show that the new algorithm converges to the viscosity solution of the problem and that its complexity is o n log n nb as it is for the fast marching method based on finite difference n and n nb being respectively the total number of nodes and the number of nodes in the narrow band a new sufficient condition for the convergence of the standard finite difference fast marching method is also given we present several tests comparing the two algorithms and other fast methods e g fast sweeping on a series of benchmarks which include the minimum time problem and the shape from shading problem

oscillation theorems for second order neutral differential equations the aim of this paper is to study the oscillation of the second order neutral differential equations e r t x t p t x t t q t x s t 0 the obtained results are based on the new comparison theorems that enable us to reduce the problem of the oscillation of the second order equation to the oscillation of the first order equation the obtained comparison principles essentially simplify the examination of the studied equations

oscillation theorems for nth order delay differential equations abstract oscillation criteria are obtained for a class of functional differential equations including the generalized emden fowler equation x n q t x g t sgn x g t 0 0 as a special case the purpose of this paper is to extend and improve known fundamental oscillation criteria for superlinear sublinear and linear differential equations with retarded arguments

oscillation of certain functional differential equations sufficient conditions are presented for all bounded solutions of the linear system of delay differential equations 1 m 1 frac d m y i t dt m sum limits j 1 n q ij y j t h jj 0 text m geqslant 1 i 1 2 n to be oscillatory where qije hjj 0 i j 1 2 n also we study the oscillatory behavior of all bounded solutions of the linear system of neutral differential equations 1 m 1 frac d m dt m y i t cy i t g sum limits j 1 n q ij y j t h 0 where c g and h are real constants and i 1 2 n

oscillation of damped pde with p laplacian in unbounded domains abstract in this paper new oscillation theorems for the damped partial differential equation pde with p laplacian div a x u p 2 u b x u p 2 u c x u p 2 u 0 are established in unbounded domains our theorems as two special cases when a i or a i b x 0 improve and complement some existing results in the literature to illustrate our main results we give some corollaries and examples

interval oscillation of a general class of second order nonlinear differential equations with nonlinear damping abstract the paper is concerned with the oscillation of a class of general type second order differential equations with nonlinear damping terms several new interval oscillation criteria are established for such a class of differential equations under quite general assumptions examples are also given to illustrate the results in particular it is shown that under some very mild conditions on k 1 k 2 and f the equation k 1 x x cos tk 2 x x x sin tf x 0 is oscillatory which extends the result obtained by kwong and wong j math anal appl 288 2003 15

associating visual textures with human perceptions using genetic algorithms this paper deals with an approach allowing to associate visual textures with given human perceptions hereby based on a forward model associating human perceptions for given visual textures the deduction of an reverse process is presented which is able to associate and characterize visual textures for given human perceptions for doing so we propose a constraint based genetic algorithm approach which is able to minimize a specific optimization problem containing constraints in form of band widths for valid individuals low level features extracted from textures in a population the constraints are determined by relationships between low level features characterizing textures in form of high dimensional approximation models additionally in each iteration step checking for valid individuals is carried out with a texture non texture classifier or by using a convex hull over a set of valid textures the whole approach is evaluated based on a real world texture set used as a start population in the genetic algorithm and by defining various kinds of human perceptions for which textures are sought represented by adjective vectors in the aesthetic space the generated individuals low level feature vectors have a high level of fitness they are quite close to the pre defined adjective vectors and a small distance to the initial population the textures synthesized based on the generated individuals are visualized and compared with textures synthesized by a time intensive direct texture mixing and re combination method based on a real world texture data base

integral averaging techniques for the oscillation of second order nonlinear differential equations abstract in this paper we enlist some known and establish some new oscillation criteria for the second order nonlinear differential equations of the form if a t x t t su p t t q t f x t 0 where the coefficients p t and q t are not assumed to be nonnegative for all large values of t these criteria are obtained by using integral averaging techniques and can be applied to some special cases where other classical oscillation results are not applicable a systematic study is attempted to extend improve and correlate a number of existing results

oscillation and asymptotic behavior of higher order delay differential equations with p laplacian like operators abstract the p laplace equations have some applications in continuum mechanics on the basis of this background detail we study oscillation and asymptotic behavior of solutions to two classes of higher order delay damped differential equations with p laplacian like operators some new criteria are presented that improve the related contributions to the subject several examples are provided to illustrate the relevance of new theorems

iterative two step genetic algorithm based method for efficient polynomial b spline surface reconstruction surface reconstruction is a very challenging problem arising in a wide variety of applications such as cad design data visualization virtual reality medical imaging computer animation reverse engineering and so on given partial information about an unknown surface its goal is to construct to the extent possible a compact representation of the surface model in most cases available information about the surface consists of a dense set of either organized or scattered 3d data points obtained by using scanner devices a today s prevalent technology in many reverse engineering applications in such a case surface reconstruction consists of two main stages 1 surface parameterization and 2 surface fitting both tasks are critical in order to recover surface geometry and topology and to obtain a proper fitting to data points they are also pretty troublesome leading to a high dimensional nonlinear optimization problem in this context present paper introduces a new method for surface reconstruction from clouds of noisy 3d data points our method applies the genetic algorithm paradigm iteratively to fit a given cloud of data points by using strictly polynomial b spline surfaces genetic algorithms are applied in two steps the first one determines the parametric values of data points the later computes surface knot vectors then the fitting surface is calculated by least squares through either svd singular value decomposition or lu methods the method yields very accurate results even for surfaces with singularities concavities complicated shapes or nonzero genus six examples including open semi closed and closed surfaces with singular points illustrate the good performance of our approach our experiments show that our proposal outperforms all previous approaches in terms of accuracy and flexibility

an intelligent noise reduction method for chaotic signals based on genetic algorithms and lifting wavelet transforms time series observed in real world is often nonlinear even chaotic however observed data is often contaminated by noise of various types to effectively extract desired information from observed data it is vital to preprocess data to reduce noise for both the analysis of dynamical systems and many potential applications of these systems in this paper we present a noise reduction approach to the problem of additive source separation characterized by wide band power spectra when one of the sources is chaotic the algorithm is based on a center based genetic algorithm cbga in lifting wavelet framework in which the cbga is used for threshold optimization this method intelligently adapts itself to various types of noise and it weighs preservation of dynamics and denoising through signal to noise ratio snr and root mean square error rmse computer simulations show that the approach is very effective in diminishing different kinds of noise and performs better in terms of visual quality as well as quantitative metrics than existing algorithms

type 1 and type 2 fuzzy inference systems as integration methods in modular neural networks for multimodal biometry and its optimization with genetic algorithms we describe in this paper a comparative study between fuzzy inference systems as methods of integration in modular neural networks for multimodal biometry these methods of integration are based on techniques of type 1 fuzzy logic and type 2 fuzzy logic also the fuzzy systems are optimized with simple genetic algorithms with the goal of having optimized versions of both types of fuzzy systems first we considered the use of type 1 fuzzy logic and later the approach with type 2 fuzzy logic the fuzzy systems were developed using genetic algorithms to handle fuzzy inference systems with different membership functions like the triangular trapezoidal and gaussian since these algorithms can generate fuzzy systems automatically then the response integration of the modular neural network was tested with the optimized fuzzy systems of integration the comparative study of the type 1 and type 2 fuzzy inference systems was made to observe the behavior of the two different integration methods for modular neural networks for multimodal biometry

optimal bilinear control of an abstract schro dinger equation well posedness of abstract quantum mechanical systems is considered and the existence of optimal control of such systems is proved first order optimality systems are derived convergence of the monotone scheme for the solution of the optimality system is proved

stable numerical schemes for solving hamilton jacobi bellman isaacs equations stable approximation schemes for solving hamilton jacobi bellman isaacs equations in r n are proposed the efficiency of numerical procedures based on such approximations is demonstrated by solving several differential games in two three and four dimensions

fuzzy spline interpolation with optimal property in parametric form in this paper we propose a new fuzzy interpolation procedure that uses cubic splines with an optimal property obtained in parametric form this fuzzy interpolation operator is also a linear operator of uniform approximation that preserves the monotonicity moreover by integrating this fuzzy cubic spline we obtain the trapezoidal quadrature rule for fuzzy henstock integrable functions

a hybrid genetic algorithm with the baldwin effect here we present a new hybrid genetic algorithm hga with the baldwin effect in the hga a local search is employed to change the fitness of individuals but the acquired improvements do not change the individual itself this local search step exploits the baldwin effect some numerical applications show that this algorithm can yield the global optimum more efficiently than commonly used hgas a theorem is presented that guarantees the convergence in probability of the new hga

local minimization algorithms for dynamic programming equations the numerical realization of the dynamic programming principle for continuous time optimal control leads to nonlinear hamilton jacobi bellman equations which require the minimization of a nonlinear mapping over the set of admissible controls this minimization is often performed by comparison over a finite number of elements of the control set in this paper we demonstrate the importance of an accurate realization of these minimization problems and propose algorithms by which this can be achieved effectively the considered class of equations includes nonsmooth control problems with ell 1 penalization which lead to sparse controls

averaging technique and nonlinear second order elliptic oscillation abstract by using the refinement of the standard integral averaging technique we obtain new oscillation criteria for certain nonlinear second order damped elliptic differential equations we do not impose any additional conditions on the damping terms except for the continuity in particular when n 1 our results extend those of rogovchenko and tuncay yu v rogovchenko f tuncay oscillation criteria for second order nonlinear differential equations with damping nonlinear analysis 69 2008 208 221 for second order nonlinear differential equations with damping to damped elliptic differential equations when n 2 our results improve the oscillation criteria of xu jia ma z xu b jia d ma oscillation theorems for elliptic equations with damping appl math comput 156 2004 93 106 for second order elliptic equations with damping four examples are provided to illustrate the relevance of the main results

an efficient policy iteration algorithm for dynamic programming equations we present an accelerated algorithm for the solution of static hamilton jacobi bellman equations related to optimal control problems our scheme is based on a classic policy iteration procedure which is known to have superlinear convergence in many relevant cases provided the initial guess is sufficiently close to the solution this limitation often degenerates into a behavior similar to a value iteration method with an increased computation time the new scheme circumvents this problem by combining the advantages of both algorithms with an efficient coupling the method starts with a coarse mesh value iteration phase and then switches to a fine mesh policy iteration procedure when a certain error threshold is reached a delicate point is to determine this threshold in order to avoid cumbersome computations with the value iteration and at the same time to ensure the convergence of the policy iteration method to the optimal solution we analyze the methods and efficient coupling in a number of examples

oscillatory behavior of solutions of certain second order nonlinear differential equations abstract in this paper some simple inequalities are used to offer sufficient conditions for the oscillation of all solutions of the differential equation formula where 0 p q with p q odd integers or p even and q odd integers several examples which dwell upon the importance of our results are also included

on kamenev type oscillation theorems for second order differential equations with damping abstract oscillation criteria for the nonlinear second order ordinary differential equation with damping x p t x f x 0 are given the results are extensions of integral averaging technique of kamenev and include earlier results of yeh yan and chen

particle based meta model for continuous breakpoint optimization in smooth local support curve fitting we compute a smooth meta model of a given set of data points based on local support free form parametric curves our method applies a particle based metaheuristic approach to determine optimal values of unknowns of the fitting curve the method does not assume any knowledge about the underlying function of data beyond the data points our approach performs well and in a fully automatic way even for underlying functions exhibiting challenging features our experiments show that our approach outperforms previous approaches in terms of generality and fitting error accuracy this paper concerns the process of computing the underlying function of a given set of data points in many cases it is not possible to obtain an analytical solution for this problem so the goal is transformed into that of computing a meta model instead in this paper we seek to compute a smooth meta model of such points based on local support free form parametric curves given an initial parameterization our method applies a particle based metaheuristic approach to determine optimal values for the breakpoints and poles of the fitting curve which is well known to be a continuous nonlinear optimization problem the performance of our approach is evaluated by its application to two illustrative examples a synthetic academic shape and a real world shape our experimental results show that the proposed scheme performs very well even for shapes with underlying functions exhibiting challenging features such as self intersections and sharp changes of curvature comparative results show that our approach outperforms previous approaches in terms of generality and fitting error accuracy