equilibrium and stability analysis of delayed neural networks under parameter uncertainties abstract this paper proposes new results for the existence uniqueness and global asymptotic stability of the equilibrium point for neural networks with multiple time delays under parameter uncertainties by using lyapunov stability theorem and applying homeomorphism mapping theorem new delay independent stability criteria are obtained the obtained results are in terms of network parameters of the neural system only and therefore they can be easily checked we also present some illustrative numerical examples to demonstrate that our result are new and improve corresponding results derived in the previous literature

on stabilized finite element methods based on the scott zhang projector circumventing the inf sup condition for the stokes problem abstract in this work we propose a stabilized finite element method that permits us to circumvent discrete inf sup conditions e g allowing equal order interpolation the type of method we propose belongs to the family of symmetric stabilization techniques which are based on the introduction of additional terms that penalize the difference between some quantities i e the pressure gradient in the stokes problem and their finite element projections the key feature of the formulation we propose is the definition of the projection to be used a non standard scott zhang projector that is well defined for l 1 functions the resulting method has some appealing features the projector is local and nested meshes or enriched spaces are not required

local projection stabilization for the oseen problem and its interpretation as a variational multiscale method we propose to apply the recently introduced local projection stabilization to the numerical computation of the oseen equation at high reynolds number the discretization is done by nested finite element spaces using a priori error estimation techniques we prove the convergence of the method the a priori estimates are independent of the local peclet number and give a sufficient condition for the size of the stabilization parameters in order to ensure optimality of the approximation when the exact solution is smooth moreover we show how this method may be cast in the framework of variational multiscale methods we indicate what modeling assumptions must be made to use the method for large eddy simulations

an efficient time splitting approximation of the navier stokes equations with lps modeling abstract in this work the solution of the navier stokes equations nse is addressed by a finite element fe local projection stabilization lps method combined with an efficient time splitting approximation strategy the focus is on the high order term by term stabilization method that has one level in the sense that it is defined on a single mesh and in which the projection stabilized structure of standard lps methods is replaced by an alternative interpolation stabilized structure the main contribution is on numerically analyzing for the cited lps method the proposed time approximation via stable velocity pressure segregation using semi implicit backward differentiation formulas bdf an overview about theoretical results from the numerical analysis of the proposed method is given by highlighting the used mathematical tools numerical studies support the analytical results and illustrate the potential of the method for the efficient and accurate simulation of turbulent flows on relatively coarse grids smooth unsteady flows are simulated with optimal order of accuracy

collision in a cross shaped domain a steady 2d navier stokes example demonstrating the importance of mass conservation in cfd abstract in the numerical simulation of the incompressible navier stokes equations different numerical instabilities can occur while instability in the discrete velocity due to dominant convection and instability in the discrete pressure due to a vanishing discrete ladyzhenskaya babuska brezzi lbb constant are well known instability in the discrete velocity due to a poor mass conservation at high reynolds numbers sometimes seems to be underestimated at least when using conforming galerkin mixed finite element methods like the taylor hood element the classical grad div stabilization for enhancing discrete mass conservation is often neglected in practical computations though simple academic flow problems showing the importance of mass conservation are well known these examples differ from practically relevant ones since specially designed force vectors are prescribed therefore we present a simple steady navier stokes problem in two space dimensions at reynolds number 1024 a colliding flow in a cross shaped domain where the instability of poor mass conservation is studied in detail and where no force vector is prescribed

dissipativity analysis for singular systems with time varying delays this paper is concerned with the dissipativity analysis problem for singular systems with time varying delays a delay dependent criterion is established to guarantee the dissipativity of the underlying systems using the delay partitioning technique all the results given in this paper are not only dependent upon the time delay but also dependent upon the number of delay partitions the effectiveness and the reduced conservatism of the derived results are demonstrated by two illustrative examples

numerical investigation on the stability of singular driven cavity flow by applying the singularity subtraction technique to the unsteady driven cavity problem the stability of the impulsively started flow is investigated without smoothing the corner singularity a second order spectral projection method allows localization of the critical reynolds number for the first hopf bifurcation in the interval 8017 6 8018 8

undecidability of subsumption in nikl abstract subsumption determining whether one concept is more general than another is known to be np hard for all reasonably expressive terminological logics but up to now the decidability of subsumption for terminological logics used in current knowledge representation systems such as nikl remained unknown this paper shows that subsumption in the terminological logic of nikl is undecidable and thus that there are no complete algorithms for subsumption or classification in nikl

robust passivity analysis of fuzzy cohen grossberg bam neural networks with time varying delays abstract this paper is concerned with the problem of passivity analysis for a class of cohen grossberg fuzzy bidirectional associative memory bam neural networks with time varying delay by employing the delay fractioning technique and linear matrix inequality optimization approach delay dependent passivity criteria are established that guarantees the passivity of fuzzy cohen grossberg bam neural networks with uncertainties the passivity condition is expressed in terms of lmis which can be easily solved by various convex optimization algorithms finally a numerical example is given to illustrate the effectiveness of the proposed result

interior penalty variational multiscale method for the incompressible navier stokes equation monitoring artificial dissipation in this paper we apply the interior penalty method analyzed in e burman and m a fernndez numer math 107 2007 no 1 39 77 mr2317827 2008c 65317 to flows at high reynolds number as a possible measure of solution quality we propose to monitor the ratio between the artificial dissipation induced by the numerical method and the computed physical dissipation for smooth flows we prove that for our method the artificial dissipation serves as an a posteriori error estimator and also that it vanishes at an optimal rate in the case of flows with multiscale features we discuss a heuristic approach relating the decay of the artificial dissipation to the decay rate of the power spectrum some numerical results in two space dimensions are presented examining the relation between the numerical dissipation and solution quality

a new approach for secure communication using constrained hyperchaotic systems a new constrained hyperchaotic system is presented a secure communication scheme using the generated chaotic signals is proposed the crls estimator for nonlinear systems is used for chaos synchronization the crls estimator and the convergence of its nonlinear update phase are analyzed simulation results demonstrate the proposed secure scheme effectiveness in this paper a new technique is developed for a typical secure communication scheme in this approach we introduce the concept of constrained hyperchaotic systems to encrypt the carrier of the data signal to be transmitted at the transmitter end two different chaotic oscillators are coupled constrained and used as a new hyperchaotic system one of the outputs of the constrained hyperchaotic system is used as a carrier for the encrypted data then the outputs of the system including the modulated carrier are encrypted using a set of pre defined encryption rules at the receiving end and after decrypting the received outputs the discrete time constrained regularized least square crls estimator is used to reconstruct the constrained hyperchaotic signals and hence retrieve the transmitted data simulation results are presented to illustrate the capability of the crls estimator in reconstructing the states of the constrained hyperchaotic system moreover the proposed secure communication scheme is applied to transmit discrete images for which the quality of the transmission process is measured by the bit error rate ber

improvements on open and traction boundary conditions for navier stokes time splitting methods we present in this paper a numerical scheme for incompressible navier stokes equations with open and traction boundary conditions in the framework of pressure correction methods a new way to enforce this type of boundary condition is proposed and provides higher pressure and velocity convergence rates in space and time than found in the present state of the art we illustrate this result by computing some numerical and physical tests in particular we establish reference solutions of a laminar flow in a geometry where a bifurcation takes place and of the unsteady flow around a square cylinder

pressure stability in fractional step finite element methods for incompressible flows abstract the objective of this paper is to analyze the pressure stability of fractional step finite element methods for incompressible flows that use a pressure poisson equation for the classical first order projection method it is shown that there is a pressure control which depends on the time step size and therefore there is a lower bound for this time step for stability reasons the situation is much worse for a second order scheme in which part of the pressure gradient is kept in the momentum equation the pressure stability in this case is extremely weak to overcome these shortcomings a stabilized fractional step finite element method is also considered and its stability is analyzed some simple numerical examples are presented to support the theoretical results

global exponential stability of cellular neural networks with variable delays for cellular neural networks with time varying delays the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the lyapunov krasovskii functional and linear matrix inequality lmi technique a novel criterion for the stability which give information on the delay dependent property is derived two examples are given to demonstrate the effectiveness of the obtained results

delay dependent exponential stability for a class of neural networks with time delays this paper is concerned with the exponential stability of a class of delayed neural networks described by nonlinear delay differential equations of the neutral type in terms of a linear matrix inequality lmi a sufficient condition guaranteeing the existence uniqueness and global exponential stability of an equilibrium point of such a kind of delayed neural networks is proposed this condition is dependent on the size of the time delay which is usually less conservative than delay independent ones the proposed lmi condition can be checked easily by recently developed algorithms solving lmis examples are provided to demonstrate the effectiveness and applicability of the proposed criteria

a stabilized finite element method for generalized stationary incompressible flows abstract in this paper we describe a finite element formulation for the numerical solution of the stationary incompressible navier stokes equations including coriolis forces and the permeability of the medium the stabilized method is based on the algebraic version of the sub grid scale approach we first describe this technique for general systems of convection diffusion reaction equations and then we apply it to the linearized flow equations the important point is the design of the matrix of stabilization parameters that the method has this design is based on the identification of the stability problems of the galerkin method and a scaling of variables argument to determine which coefficients must be included in the stabilization matrix this together with the convergence analysis of the linearized problem leads to a simple expression for the stabilization parameters in the general situation considered in the paper the numerical analysis of the linearized problem also shows that the method has optimal convergence properties

design of state estimator for neural networks of neutral type in this paper the design problem of state estimator for a class of neural networks of neutral type is studied a delay dependent linear matrix inequality lmi criterion for existence of the estimator is proposed by using the lyapunov method the criterion can be easily solved by various convex optimization algorithms a numerical example with simulation results is given to show the effectiveness of proposed method

algebraic fractional step schemes with spectral methods for the incompressible navier stokes equations the numerical investigation of a recent family of algebraic fractional step methods for the solution of the incompressible time dependent navier stokes equations is presented these methods are improved versions of the yosida method proposed in a quarteroni f saleri a veneziani factorization methods for the numerical approximation of navier stokes equations comput methods appl mech engrg 188 1 3 2000 505 526 a quarteroni f saleri a veneziani j math pures appl 9 78 5 1999 473 503 and one of them the yosida4 method is proposed in this paper for the first time they rely on an approximate lu block factorization of the matrix obtained after the discretization in time and space of the navier stokes system yielding a splitting in the velocity and pressure computation in this paper we analyze the numerical performances of these schemes when the space discretization is carried out with a spectral element method with the aim of investigating the impact of the splitting on the global accuracy of the computation

further result on asymptotic stability criterion of cellular neural networks with time varying discrete and distributed delays based on a recent work and the linear matrix inequality lmi optimization approach we extend the recent work on global asymptotic stability of a class of neural networks to uncertain cellular neural networks with time varying discrete and distributed delays

numerical analysis of a finite element projection based vms turbulence model with wall laws abstract this paper deals with the numerical analysis of a finite element projection based vms turbulence model that includes general non linear wall laws only a single mesh and interpolation operators on a virtual coarser mesh are needed to implement the model we include a projection stabilization of pressure to use the same interpolation for velocity and pressure good accuracy is obtained with benchmark turbulent flow problems on coarse grids that justify the interest of this approach also the model solves smooth flows with optimal accuracy

on the relative expressiveness of description logics and predicate logics abstract it is natural to view concept and role definitions in description logics as expressing monadic and dyadic predicates in predicate calculus we show that the descriptions built using the constructors usually considered in the dl literature are characterized exactly as the predicates definable by formulas in tl3 the subset of first order predicate calculus with monadic and dyadic predicates which allows only three variable symbols in order to handle number bounds we allow numeric quantifiers and for transitive closure of roles we use infinitary disjunction using previous results in the literature concerning languages with limited numbers of variables we get as corollaries the existence of formulas of fopc which cannot be expressed as descriptions we also show that by omitting role composition descriptions express exactly the formulas in tl2 which is known to be decidable

stable analysis for neural networks set valued mapping method by constructing some complete metric spaces this paper investigates the stable problem for a class of neural networks on the basis of set valued mapping theory by introducing the notion of essential equilibrium point some sufficient and necessary criteria guaranteeing the existence and stability of the equilibrium point are established when the activation function and uncertain parameter vary continuously different from most of previous works on the stability problem of neural network the feature of the method used in this paper does not depend on any lyapunov functional

an epistemic operator for description logics abstract description logics also called terminological logics or concept languages are fragments of first order logic that provide a formal account of the basic features of frame based systems however there are aspects of frame based systems such as nonmonotonic reasoning and procedural rules that cannot be characterized in a standard first order framework such features are needed for real applications and a clear understanding of the logic underlying them is necessary for principled implementations we show how description logics enriched with an epistemic operator can formalize such aspects the logic obtained is a fragment of a first order nonmonotonic modal logic we show that the epistemic operator formalizes procedural rules as provided in many knowledge representation systems and enables sophisticated query formulation including various forms of closed world reasoning we provide an effective procedure for answering epistemic queries posed to a knowledge base expressed in a description logic and extend this procedure in order to deal with rules we also address the computational complexity of reasoning with the epistemic operator identifying cases in which an appropriate use of the epistemic operator can help in decreasing the complexity of reasoning

an additive schwarz method type theory for lions s algorithm and a symmetrized optimized restricted additive schwarz method optimized schwarz methods osms are very popular methods which were introduced by p l lions in on the schwarz alternating method iii a variant for nonoverlapping subdomains in 3rd international symposium on domain decomposition methods for partial differential equations houston tx 1989 t f chan r glowinski j periaux and o widlund eds siam philadelphia 1990 pp 202 223 for elliptic problems and by b despres in c r acad sci paris ser i math 311 1990 pp 313 316 for propagative wave phenomena we give here a theory for lions s algorithm that is the genuine counterpart of the theory developed over the years for the schwarz algorithm the first step is to introduce a symmetric variant of the optimized restricted additive schwarz oras algorithm a st cyr m j gander and s j thomas siam j sci comput 29 2007 pp 2402 2425 that is suitable for the analysis of a two level method then we build a coarse space for which the convergence rate of the two level m

bifurcation analysis of incompressible flow in a driven cavity by the newton picard method knowledge of the transition point of steady to periodic flow is becoming increasingly important in the study of laminar turbulent flow transition or fluid structure interaction such knowledge becomes available through the newton picard method a method related to the recursive projection method here this method is applied to study the bifurcation behavior of the flow in a driven cavity between reynolds number 7500 and 10 000 for the time discretization the method is used and for the space discretization a robust finite volume method the implicit relations occurring after linearization are solved by the multilevel ilu solver mrilu the results presented in this paper confirm findings from earlier work with respect to the transition point they give more detailed information on unstable modes and clarify time series found by others

korn s inequalities and their applications in continuum mechanics korn s inequalities have played a central role in the development of linear elasticity not only in connection with the basic theoretical issues such as existence and uniqueness but also in a variety of applications the korn inequalities and other related inequalities for integrals of quadratic functionals also arise in the analysis of viscous incompressible fluid flow the dimensionless optimal constants appearing in these inequalities the korn constants depend only on the shape of the domains of concern information on the geometric dependence of these constants is essential in applications in this review article we summarize the major results on korn s inequalities for bounded domains in two and three dimensions with emphasis on results concerning the korn constants some applications in continuum mechanics are also described

robust synchronization of fractional order unified chaotic systems via linear control a new scheme for accomplishing synchronization between two fractional order unified chaotic systems is proposed in this paper the scheme does not require that the nonlinear dynamics of the synchronization error system must be eliminated moreover the parameter of the systems does not have to be known a controller is a linear feedback controller which is simple in implementation it is designed based on an lmi condition the lmi condition guarantees that the synchronization between the slave system and the master system is achieved numerical simulations are performed to demonstrate the effectiveness of the proposed scheme

improved results on robust exponential stability criteria for neutral type delayed neural networks abstract in this paper we investigate the problem of robust global exponential stability analysis for a class of neutral type neural networks the interval time varying delays allow for both slow and fast time varying delays the values of the time varying uncertain parameters are assumed to be bounded within given compact sets improved global exponential stability condition is derived by employing new lyapunov krasovskii functional and the integral inequality the developed nominal and robust stability criteria is delay dependent and characterized by linear matrix inequalities lmis the developed results are less conservative than previous published ones in the literature which are illustrated by representative numerical examples

existence and stability of almost periodic solutions of hopfield neural networks with continuously distributed delays abstract in this paper the global stability and almost periodicity are investigated for hopfield neural networks with continuously distributed neutral delays some sufficient conditions are obtained for the existence and globally exponential stability of almost periodic solution by employing fixed point theorem and differential inequality techniques the results of this paper are new and they complement the previously known ones finally an example is given to demonstrate the effectiveness of our results

stability criteria for bam neural networks with leakage delays and probabilistic time varying delays this paper is concerned with the stability criteria for bidirectional associative memory bam neural networks with leakage time delay and probabilistic time varying delays by establishing a stochastic variable with bernoulli distribution the information of probabilistic time varying delay is transformed into the deterministic time varying delay with stochastic parameters based on the lyapunov krasovskii functional and stochastic analysis approach delay probability distribution dependent sufficient conditions are derived to achieve the globally asymptotically mean square stable of the considered bam neural networks the criteria are formulated in terms of a set of linear matrix inequalities lmis which can be checked efficiently by use of some standard numerical packages finally a numerical example and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results

passivity of delayed reaction diffusion networks with application to a food web model this paper is concerned with the passivity problem of a class of delayed reaction diffusion networks in which the input and output variables are varied with the time and space variables firstly two new passivity definitions are proposed which are totally different from some existing concepts of passivity then we establish several criteria for the passivity input strict passivity and output strict passivity by using the lyapunov functional method combined with the inequality techniques and also reveal the relationship between passivity and stability of the reaction diffusion networks moreover these results are applied to investigate the asymptotic stability and control design of a food web model with time delay and reaction diffusion terms numerical simulations are presented finally to demonstrate the effectiveness of the proposed results

new robust stability results for bidirectional associative memory neural networks with multiple time delays in this paper the robust stability problem is investigated for a class of bidirectional associative memory bam neural networks with multiple time delays by employing suitable lyapunov functionals and using the upper bound norm for the interconnection matrices of the neural network system some novel sufficient conditions ensuring the existence uniqueness and global robust stability of the equilibrium point are derived the obtained results impose constraint conditions on the system parameters of neural network independent of the delay parameters some numerical examples and simulation results are given to demonstrate the applicability and effectiveness of our results and to compare the results with previous robust stability results derived in the literature

new results for global stability of a class of neutral type neural systems with time delays this paper studies the global convergence properties of a class of neutral type neural networks with discrete time delays this class of neutral systems includes cohen grossberg neural networks hopfield neural networks and cellular neural networks based on the lyapunov stability theorems some delay independent sufficient conditions for the global asymptotic stability of the equilibrium point for this class of neutral type systems are derived it is shown that the results presented in this paper for neutral type delayed neural networks are the generalization of a recently reported stability result a numerical example is also given to demonstrate the applicability of our proposed stability criteria

improved global robust stability of interval delayed neural networks via split interval generalizations abstract the problem of global robust stability of hopfield type delayed neural networks with the intervalized network parameters is revisited recently a computationally tractable i e linear matrix inequality lmi based global robust stability criterion derived from an earlier criterion based on dividing the given interval into more that two intervals has been presented in the present paper generalizations i e division of the given interval into m intervals where m is an integer greater than or equal to 2 is considered and some new lmi based global robust stability criteria are derived it is shown that in some cases m 2 may not suffice i e m 2 may be needed to realize the improvement an example showing the effectiveness of the proposed generalization is given the paper also provides a complete and systematic explanation of the split interval idea

new stability criteria for neural networks with time varying delays abstract this paper is concerned with the stability analysis problem of neural networks with time delays the delay intervals d t 0 and h 0 are divided into m subintervals with equal length some free matrices are introduced to build the relationship among the elements of the resultant matrix inequalities with the above operations the new stability criteria are built for the general class of neural networks the conditions are presented in the form of linear matrix inequalities lmis which can be solved by the numerically efficient matlab lmi toolbox several examples are provided to show that our methods are much less conservative than recently reported ones

synchronization analysis in an array of asymmetric neural networks with time varying delays and nonlinear coupling in this paper the global exponential synchronization is investigated for an array of asymmetric neural networks with time varying delays and nonlinear coupling assuming neither the differentiability for time varying delays nor the symmetry for the inner coupling matrices by employing a new lyapunov krasovskii functional applying the theory of kronecker product of matrices and the technique of linear matrix inequality lmi a delay dependent sufficient condition in lmis form for checking global exponential synchronization is obtained the proposed result generalizes and improves the earlier publications an example with chaotic nodes is given to show the effectiveness of the obtained result

combining deduction and model checking into tableaux and algorithms for converse pdl this paper presents a prefixed tableaux calculus for propositional dynamic logic with converse based on a combination of different techniques such as prefixed tableaux for modal logics and model checkers for calculus we prove the correctness and completeness of the calculus and illustrate its features we also discuss the transformation of the tableaux method naively nexptime into an exptime algorithm

time dependent subscales in the stabilized finite element approximation of incompressible flow problems abstract in this paper we analyze a stabilized finite element approximation for the incompressible navier stokes equations based on the subgrid scale concept the essential point is that we explore the properties of the discrete formulation that results allowing the subgrid scales to depend on time this apparently natural idea avoids several inconsistencies of previous formulations and also opens the door to generalizations

stability analysis of fractional order complex valued neural networks with both leakage and discrete delays in this paper the problem of uniform stability for fractional order complex valued neural networks with both leakage and discrete delays is considered base on the contracting mapping principle a sufficient condition is proposed for the existence and uniqueness of the equilibrium point of the addressed neural networks by employing analysis technique some delay dependent criteria are established for checking the global uniform stability of the fractional order complex valued neural networks two numerical examples are presented to demonstrate the validity and feasibility of the proposed results

exponential passivity of bam neural networks with time varying delays the problem of delay dependent exponential passivity analysis is investigated for bam neural networks with time varying delays by establishing a suitable augmented lyapunov krasovskii function and a novel sufficient condition is obtained to guarantee the exponential stability of the considered system the several exponential stability criterion proposed in this paper is simpler and effective a numerical example is provided to demonstrate the feasibility and effectiveness of our results

passivity based control for hopfield neural networks using convex representation this paper considers the problem of passivity based controller design for hopfield neural networks by making use of a convex representation of nonlinearities a feedback control scheme based on passivity and lyapunov theory is presented a criterion for existence of the controller is given in terms of linear matrix inequality lmi which can be easily solved by a convex optimization problem an example and its numerical simulation are given to show the effectiveness of the proposed method

an analysis of global asymptotic stability of delayed cellular neural networks in this paper a new sufficient condition is given for the uniqueness and global asymptotic stability of the equilibrium point for delayed cellular neural networks dcnns this condition imposes constraints on the feedback and delayed feedback matrices of a dcnn independently of the delay parameter this result is also compared with the previous results derived in the literature

new and improved results on stability of static neural networks with interval time varying delays abstract in this paper the problem of stability analysis for static neural networks with interval time varying delays is considered by the consideration of new augmented lyapunov functionals new and improved delay dependent stability criteria to guarantee the asymptotic stability of the concerned networks are proposed with the framework of linear matrix inequalities lmis which can be solved easily by standard numerical packages the enhancement of the feasible region of the proposed criteria is shown via two numerical examples by the comparison of maximum delay bounds

a three level finite element method for the instationary incompressible navier stokes equations we present a two and a three level finite element method for the numerical simulation of incompressible flow governed by the navier stokes equations within the theoretical framework of the variational multiscale method and exploiting the concept of residual free bubbles we propose a separation of three different scale groups namely large resolved scales small resolved scales and unresolved scales the resolution of the large and small scales takes place on levels 1 and 2 with the aid of diverse approaches the dynamic calculation of a subgrid viscosity representing the effect of the unresolved scales constitutes level 3 of our algorithm the proposed algorithm is tested for various laminar flow situations and compared to the results obtained via an unusual stabilized finite element method it is supposed to be the basic scheme also for turbulent flow in a subsequent study

optimized multiplicative additive and restricted additive schwarz preconditioning we demonstrate that a small modification of the multiplicative additive and restricted additive schwarz preconditioner at the algebraic level motivated by optimized schwarz methods defined at the continuous level leads to a significant reduction in the iteration count of the iterative solver numerical experiments using finite difference and spectral element discretizations of the positive definite helmholtz problem and an idealized climate simulation illustrate the effectiveness of the new approach

discontinuous galerkin time stepping with local projection stabilization for transient convection diffusion reaction problems abstract a time dependent convection diffusion reaction problem is discretized in space by a continuous finite element method with local projection stabilization and in time by a discontinuous galerkin method we present error estimates for the semidiscrete problem after discretizing in space only and for the fully discrete problem numerical tests confirm the theoretical results

an assessment of two models for the subgrid scale tensor in the rational les model les models seek to approximate the large scales of a flow which are defined by a space average u p of the velocity u and the pressure p of the flow a natural question which arises is given reliable data for u p how accurate is the approximation of u p by the solution computed with a les model this paper presents numerical studies of this question at a 2d and 3d mixing layer problem for the rational les model with two types of models for the subgrid scale tensor the smagorinsky model and a model proposed by iliescu and layton whereas in the 2d mixing layer problem the model by iliescu and layton showed better results the behaviour of both models was similar in the 3d mixing layer problem

robust h infinity control for a class of neutral type systems via sliding mode observer in this paper the problem of observer based h infinity integral sliding mode control ismc is investigated for a class of uncertain neutral type systems with time delay ntstd an ismc strategy is put forward based on the sliding mode observer a new sufficient condition of robust asymptotic stability for the overall systems composed of the error system and sliding mode dynamics with disturbance attenuation level is derived via linear matrix inequality lmi then a smc law is designed such that the reachability of the sliding surface defined in the state estimate space can be guaranteed finally a simulation example is presented to demonstrate the feasibility of the obtained result

an improved secure communication scheme based passive synchronization of hyperchaotic complex nonlinear system in this paper an improved secure communication scheme is proposed based on passive synchronization of hyperchaotic complex nonlinear system the hyperchaotic complex lu system is employed to encrypt the emitted signal comparing with the existing approaches the useful information in our work can be unbounded in the transmitter the original information signal is modulated into one parameter of hyperchaotic complex lu system and it is assumed that the parameter of the receiver system is unknown in the receiver based on the passivity theory the controllers and corresponding parameter update rule are designed to make two identical hyperchaotic complex lu systems asymptotically synchronized and identify the unknown parameter simultaneously the information signal can be recovered accurately by the estimated parameter corresponding theoretical proofs and numerical simulations demonstrate the feasibility and effectiveness of the proposed method it is also shown that the presented secure communication scheme is robust against different channel noise

a generalization of the local projection stabilization for convection diffusion reaction equations we introduce a generalization of the local projection stabilization for steady scalar convection diffusion reaction equations which allows us to use local projection spaces defined on overlapping sets this enables us to define the local projection method without the need of a mesh refinement or an enrichment of the finite element space and increases the robustness of the local projection method with respect to the choice of the stabilization parameter the stabilization term is slightly modified which leads to an optimal estimate of the consistency error even if the stabilization parameters scale correctly with respect to convection diffusion and mesh width we prove that the bilinear form corresponding to the method satisfies an inf sup condition with respect to the supg norm and establish an optimal error estimate in this norm the theoretical considerations are illustrated by numerical results

a term by term stabilization algorithm for finite element solution of incompressible flow problems this paper introduces a stabilization technique for finite element numerical solution of 2d and 3d incompressible flow problems it may be applied to stabilize the discretization of the pressure gradient and also of any individual operator term such as the convection curl or divergence operators with specific levels of numerical diffusion for each one of them its computational complexity is reduced with respect to usual residual based stabilization techniques we consider piecewise affine finite elements for which we obtain optimal error bounds for steady navier stokes and also for generalized stokes equations including convection we include some numerical experiment in well known 2d test cases that show its good performances

lmi optimization approach on stability for delayed neural networks of neutral type in this paper the global asymptotic stability of delayed cellular neural networks of neutral type is investigated a novel delay dependent criterion for the stability using the lyapunov stability theory and linear matrix inequality lmi framework is presented since the condition is dependent on the size of time delay it is usually less conservative than delay independent ones two numerical examples are given to show the effectiveness of proposed method

existence and global asymptotic stability of positive periodic solution of delayed cohen grossberg neural networks abstract in this paper a class of periodic cohen grossberg neural networks with discrete and distributed time varying delays is considered by an extension of the lyapunov krasovskii functional method a novel criterion for the existence and uniqueness and global asymptotic stability of positive periodic solution is derived in terms of m matrix without any restriction on uniform positiveness of the amplification functions comparison and illustrative examples are given to illustrate the effectiveness of the obtained results

improved delay dependent stability results of recurrent neural networks abstract by using the fact that the activation functions are sector bounded and a tighter inequality this paper presents a new method to the stability analysis of a class of recurrent neural networks rnns with time varying delays this method includes more the slope of activation functions and less variables matrices in constructed lyapunov krasovskii functional with the present stability conditions the computational burden and conservatism are largely reduced both theoretical analysis and numerical example are given to illustrate the effectiveness and the benefits of the proposed method

an overview of projection methods for incompressible flows a series of numerical issues related to the analysis and implementation of fractional step methods for incompressible flows are addressed in this paper these methods are often referred to in the literature as projection methods and can be classified into three classes namely the pressure correction methods the velocity correction methods and the consistent splitting methods for each class of schemes theoretical and numerical convergence results available in the literature are reviewed and open questions are discussed the essential results are summarized in a table which could serve as a useful reference to numerical analysts and practitioners published by elsevier b v msc 65n35 65n22 65f05 35j05

attributive concept descriptions with complements abstract we investigate the consequences of adding unions and complements to attributive concept descriptions employed in terminological knowledge representation languages it is shown that deciding coherence and subsumption of such descriptions are pspace complete problems that can be decided with linear space

passivity criteria for continuous time neural networks with mixed time varying delays abstract this paper is concerned with the problem of passivity analysis for uncertain continuous time neural networks with mixed time varying delays the mixed time varying delays consist of both discrete and distributed delays in which the discrete delays are assumed to be varying within a given interval in addition the uncertainties are assumed to be norm bounded by employing a novel lyapunov krasovskii functional new passivity delay interval dependent criteria are established to guarantee the passivity performance when estimating an upper bound of the derivative of the lyapunov krasovskii functional we handle the terms related to the discrete and distributed delays appropriately so as to develop less conservative results these passivity conditions are presented in terms of linear matrix inequalities which can be easily solved via standard numerical software some numerical examples are given to illustrate the effectiveness of the proposed method

a new criterion of delay dependent asymptotic stability for hopfield neural networks with time delay in this brief the problem of global asymptotic stability for delayed hopfield neural networks hnns is investigated a new criterion of asymptotic stability is derived by introducing a new kind of lyapunov krasovskii functional and is formulated in terms of a linear matrix inequality lmi which can be readily solved via standard software this new criterion based on a delay fractioning approach proves to be much less conservative and the conservatism could be notably reduced by thinning the delay fractioning an example is provided to show the effectiveness and the advantage of the proposed result

robust stability criteria for discrete time switched neural networks with various activation functions abstract this paper is concerned with the problem of robust stabilization and h control for a class of discrete time switched neural networks with various activation functions and mixed time delays by using the average dwell time approach together with the multiple lyapunov function technique we propose a state feedback controller to guarantee that the switched neural networks is robustly exponentially stable with the disturbance attenuation level 0 about its equilibrium point for all admissible uncertainties the obtained results are formulated in terms of linear matrix inequalities lmis which can be easily verified by the matlab lmi control toolbox finally numerical examples with simulation result are given to illustrate the effectiveness and applicability of the obtained results

direct delay decomposition approach to synchronization of chaotic fuzzy cellular neural networks with discrete unbounded distributed delays and markovian jumping parameters in this paper the problem of synchronization of chaotic fuzzy cellular neural networks fcnns with discrete unbounded distributed delays and markovian jumping parameters mjps is investigated sufficient delay dependent stability criteria are obtained in terms of linear matrix inequalities lmis to ensure the chaotic delayed fcnns to be stochastic asymptotically synchronous with the help of free weighting matrix and some inequality techniques the information of the delayed plant states can be taken into full consideration here the delay interval is decomposed into two subintervals by using the tuning parameter such that 0 1 by developing a delay decomposition approach and constructing suitable lyapunov krasovskii functional lkf sufficient conditions for synchronization are established for each subinterval numerical example and its simulations are provided to demonstrate the effectiveness and less conservatism of the derived results

global stability for cellular neural networks with time delay a sufficient condition related to the existence of a unique equilibrium point and its global asymptotic stability for cellular network networks with delay dcnns is derived it is shown that the condition relies on the feedback matrices and is independent of the delay parameter furthermore this condition is less restrictive than that given in the literature

error analysis of pressure correction schemes for the time dependent stokes equations with open boundary conditions the incompressible stokes equations with prescribed normal stress open boundary conditions on part of the boundary are considered it is shown that the standard pressure correction method is not suitable for approximating the stokes equations with open boundary conditions whereas the rotational pressure correction method yields reasonably good error estimates these results appear to be the first ever published for splitting schemes with open boundary conditions numerical results in agreement with the error estimates are presented

a new stability criterion for bidirectional associative memory neural networks of neutral type in the paper the global asymptotic stability of equilibrium is considered for continuous bidirectional associative memory bam neural networks of neutral type by using the lyapunov method a new stability criterion is derived in terms of linear matrix inequality lmi to ascertain the global asymptotic stability of the bam the lmi can be solved easily by various convex optimization algorithms a numerical example is illustrated to verify our result

stability analysis of static recurrent neural networks with interval time varying delay the problem of stability analysis of static recurrent neural networks with interval time varying delay is investigated in this paper a new lyapunov functional which contains some new double integral and triple integral terms are introduced information about the lower bound of the delay is fully used in the lyapunov functional integral and double integral terms in the derivative of the lyapunov functional are divided into some parts to get less conservative results some sufficient stability conditions are obtained in terms of linear matrix inequality lmi numerical examples are given to illustrate the effectiveness of the proposed method

the complexity of concept languages abstract a basic feature of terminological knowledge representation systems is to represent knowledge by means of taxonomies here called terminologies and to provide a specialized reasoning engine to do inferences on these structures the taxonomy is built through a representation language called a concept language or description logic which is given a well defined set theoretic semantics the efficiency of reasoning has often been advocated as a primary motivation for the use of such systems the main contributions of the paper are 1 a complexity analysis of concept satisfiability and subsumption for a wide class of concept languages 2 algorithms for these inferences that comply with the worst case complexity of the reasoning task they perform

improved delay dependent stability criterion for neural networks with time varying delay in this paper the problem of delay dependent asymptotic stability criterion for neural networks with time varying delay has been considered a new class of lyapunov functional which contains a triple integral term is constructed to derive some new delay dependent stability criteria the obtained criteria are less conservative because free weighting matrices method and a convex optimization approach are considered finally numerical examples are given to illustrate the effectiveness of the proposed method

synchronization of unified chaotic system based on passive control chaos synchronization in the unified chaotic system was discussed using passive control on the basis of the property of the passive system the passive controller is designed and synchronization of two identical unified chaotic systems with different initial conditions is realized simulation results for two lorenz two lu and two chen chaotic systems are provided to show the effectiveness of the proposed synchronization method

design of state estimator for neural networks with leakage discrete and distributed delays abstract in this paper the design problem of state estimator for neural networks with mixed time varying delays and leakage delays has been investigated by using appropriate model transformation that shifts the considered systems into the neutral type time delay systems adapting a new lyapunov krasovskii functional which takes into account the range of time delay and by making use of some inequality techniques delay dependent criteria are developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable the criteria are formulated in terms of a set of linear matrix inequalities lmis which can be checked efficiently by use of some standard numerical packages finally three numerical examples and its simulations are given to demonstrate the usefulness and effectiveness of the presented results

finite time stability of a class of non autonomous neural networks with heterogeneous proportional delays in this paper the problem of finite time stability analysis for a class of non autonomous neural networks with heterogeneous proportional delays is considered by introducing a novel constructive approach we derive new explicit conditions in terms of matrix inequalities ensuring that the state trajectories of the system do not exceed a certain threshold over a pre specified finite time interval as a result we also obtain conditions for the power rate global stability of the system numerical examples are given to demonstrate the effectiveness and less restrictiveness of the results obtained in this paper

lmi conditions for global asymptotic stability results for neutral type neural networks with distributed time delays abstract in this paper the global asymptotic stability of neutral type neural networks with unbounded distributed delays is analyzed by utilizing the lyapunov krasovskii functional and the linear matrix inequality lmi approach a new sufficient condition ensuring the global asymptotic stability for neutral type neural networks is obtained by using the powerful matlab lmi toolbox two examples are provided to illustrate the applicability of the stability results

the kl one family abstract the knowledge representation system kl one has been one of the most influential and imitated knowledge representation systems in the artificial intelligence community begun at bolt beranek and newman in 1978 kl one pioneered the development of taxonomic representations that can automatically classify and assimilate new concepts based on a criterion of terminological subsumption this theme generated considerab interest in both the formal community and a large community of potential users the kl one community has since expanded to include many systems at many institutions and in many different countries this paper introduces the kl one family and discusses some of the main themes explored by kl one and its successors we give an overview of current research describe some of the systems that have been developed and outline some future research directions

two theses of knowledge representation language restrictions taxonomic classification and the utility of representation services abstract levesque and brachman argue that in order to provide timely and correct responses in the most critical applications general purpose knowledge representation systems should restrict their languages by omitting constructs which require nonpolynomial worst case response times for sound and complete classification they also separate terminological and assertional knowledge and restrict classification to purely terminological information we demonstrate that restricting the terminological language and classifier in these ways limits these general purpose facilities so severely that they are no longer generally applicable we argue that logical soundness completeness and worst case complexity are inadequate measures for evaluating the utility of representation services and that this evaluation should employ the broader notions of utility and rationality found in decision theory we suggest that general purpose representation services should provide fully expressive languages classification over relevant contingent information approximate forms of classification involving defaults and rational management of inference tools

chaos control and synchronization of unified chaotic systems via linear control chaos control and synchronization in the unified chaotic systems is discussed in this paper based on the stability theory of a cascade connected system control laws are presented to achieve chaos control and synchronization respectively the advantage of the proposed controllers is that they are linear and have lower dimensions than that of the states simulation results for lorenz lu and chen chaotic systems are provided to illustrate the effectiveness of the proposed scheme

sensitivity of optimal control for diffusion hopfield neural network in the presence of perturbation abstract with the wide investigation of hopfield neural network hnn and its control problems this paper is to control diffusion hnn system in the presence of perturbation disturbance uncertainties in the control field in particular it is try to answer the most interesting question on the sensitivity of these perturbations both in theoretical and computational aspects