asymptotic stability of impulsive stochastic partial differential equations with infinite delays in this paper we study the existence and asymptotic stability in pth moment of mild solutions to nonlinear impulsive stochastic partial differential equations with infinite delay by employing a fixed point approach sufficient conditions are derived for achieving the required result these conditions do not require the monotone decreasing behaviour of the delays

a high resolution fundamental frequency determination based on phase changes of the fourier transform the constant q transform described recently j c brown and m s puckette an efficient algorithm for the calculation of a constant q transform j acoust soc am 92 2698 2701 1992 has been adapted so that it is suitable for tracking the fundamental frequency of extremely rapid musical passages for this purpose the calculation described previously has been modified so that it is constant frequency resolution rather than constant q for lower frequency bins this modified calculation serves as the input for a fundamental frequency tracker similar to that described by brown j c brown musical fundamental frequency tracking using a pattern recognition method j acoust soc am 92 1394 1402 1992 once the fast fourier transform fft bin corresponding to the fundamental frequency is chosen by the frequency tracker an approximation is used for the phase change in the fft for a time advance of one sample to obtain an extremely precise value for this frequency graphical examples are given for musical passages by a violin executing vibrato and glissando where the fundamental frequency changes are rapid and continuous

stochastic stability of neutral type markovian jumping bam neural networks with time varying delays abstract in this paper stochastic stability of neutral type markovian jumping bidirectional associative memory bam neural networks is investigated the jumping parameters are modeled as a continuous time discrete state markov chain the activation functions are supposed to be bounded and globally lipschitz continuous furthermore based on the lyapunov krasovskii functional a linear matrix inequality lmi approach is developed to establish sufficient conditions and novel delay dependent conditions are established for the stochastic asymptotic stability of markovian jumping bam neural networks the condition is presented in terms of linear matrix inequalities lmis which can be easily checked by using matlab lmi toolbox finally numerical examples are provided to show the effectiveness of the main results

on the stability of the stochastic parabolic ito equation with delay and markovian jump we present a new result concerning the stability of the stochastic parabolic ito equation subject to homogenous white noise our main results state that this system is exponentially stable by means of a new lyapunov krasovskii functional and a linear matrix inequality lmi a numerical example is exploited to show the usefulness of the derived lmi based stability

review of options for structural design sensitivity analysis part 1 linear systems the paper reviews options for structural design sensitivity analysis including global finite differences continuum derivatives discrete derivatives and computational or automated differentiation the objective is to put these different approaches to design sensitivity analysis in the context of accuracy and consistency computational cost and implementation options and effort linear static analysis and transient dynamic analysis are reviewed in a separate appendix special attention is paid to the semi analytical method a future paper will address design sensitivity analysis in nonlinear structural problems

global asymptotic stability of recurrent neural networks with multiple time varying delays in this paper several sufficient conditions are established for the global asymptotic stability of recurrent neural networks with multiple time varying delays the lyapunov krasovskii stability theory for functional differential equations and the linear matrix inequality lmi approach are employed in our investigation the results are shown to be generalizations of some previously published results and are less conservative than existing results the present results are also applied to recurrent neural networks with constant time delays

second order sensitivity analysis in vibration and buckling problems a perturbation approach for the first and second order sensitivity analysis of eigenvalue problems as they arise in buckling and vibration of structural systems is presented a particular feature introduced in the formulation is the dependence of all matrices that model the problem not only on the design parameter but also on a pre critical state thus the sensitivity of the response of the fundamental path in buckling problems or a pre stressed state in vibration problems are introduced in the analysis two techniques are considered in this work the direct and the adjoint methods first and second order sensitivity equations for eigenvalues and eigenvectors are obtained and it is shown that second order sensitivity of an eigenvalue can be accomplished by using only one adjoint problem

synchronization transitions on scale free neuronal networks due to finite information transmission delays we investigate front propagation and synchronization transitions in dependence on the information transmission delay and coupling strength over scale free neuronal networks with different average degrees and scaling exponents as the underlying model of neuronal dynamics we use the efficient rulkov map with additive noise we show that increasing the coupling strength enhances synchronization monotonously whereas delay plays a more subtle role in particular we found that depending on the inherent oscillation frequency of individual neurons regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases these delay induced synchronization transitions manifest as well expressed minima in the measure for spatial synchrony appearing at every multiple of the oscillation frequency larger coupling strengths or average degrees can broaden the region of regular propagating fronts by a given information transmission delay and further improve synchronization these results are robust against variations in system size intensity of additive noise and the scaling exponent of the underlying scale free topology we argue that fine tuned information transmission delays are vital for assuring optimally synchronized excitatory fronts on complex neuronal networks and indeed they should be seen as important as the coupling strength or the overall density of interneuronal connections we finally discuss some biological implications of the presented results

delay dependent stochastic stability criteria for markovian jumping neural networks with mode dependent time varying delays and partially known transition rates abstract in this paper the problem of stochastic stability criterion of markovian jumping neural networks with mode dependent time varying delays and partially known transition rates is considered some new delay dependent stability criteria are derived by choosing a new class of lyapunov functional the obtained criteria are less conservative because free weighting matrices method and a convex optimization approach are considered finally a numerical example is given to illustrate the effectiveness of the proposed method

on conservation laws of continuum mechanics abstract a unified variational formulation is advanced leading to field equations and conservation laws in general mechanical continua the formulation is applicable to dynamic processes in any medium which admits a lagrangian as a result of the procedure employed physical or canonical momenta emerge on the same level as material momenta the simplicity and transparency of the relations derived is a consequence of strict separation of descriptions in physical and material space which precludes the use of displacement as a field variable one of the results shows that a distinction between field equations or equations of motion and conservation laws is no longer essential and all basic relations are in fact balance laws

necessary and sufficient conditions for analysis and synthesis of markov jump linear systems with incomplete transition descriptions this technical note is concerned with exploring a new approach for the analysis and synthesis for markov jump linear systems with incomplete transition descriptions in the study not all the elements of the transition rate matrices trms in continuous time domain or transition probability matrices tpms in discrete time domain are assumed to be known by fully considering the properties of the trms and tpms and the convexity of the uncertain domains necessary and sufficient criteria of stability and stabilization are obtained in both continuous and discrete time numerical examples are used to illustrate the results

periodic oscillatory solution of bidirectional associative memory networks with delays periodic oscillatory phenomena of bidirectional associative memory bam networks with axonal signal transmission delays are investigated by constructing suitable lyapunov functionals and some analysis techniques some simple sufficient conditions are derived ensuring the existence and uniqueness of periodic oscillatory solutions of the bam with delays and all other solutions of the bam converge exponentially to a periodic oscillatory solution these conditions are presented in terms of system parameters and have an important leading significance in the design and applications of periodic oscillatory neural circuits for the bam with delays

novel adaptive strategies for synchronization of linearly coupled neural networks with reaction diffusion terms in this paper two types of linearly coupled neural networks with reaction diffusion terms are proposed we respectively investigate the adaptive synchronization of these two types of complex network models with local information of node dynamics some novel adaptive strategies to tune the coupling strengths among network nodes are designed by constructing appropriate lyapunov functionals and using inequality techniques several sufficient conditions are given for reaching synchronization by using the designed adaptive laws finally two examples with numerical simulations are provided to demonstrate the effectiveness of the theoretical results

passivity and stability analysis of reaction diffusion neural networks with dirichlet boundary conditions this paper is concerned with the passivity and stability problems of reaction diffusion neural networks rdnns in which the input and output variables are varied with the time and space variables by utilizing the lyapunov functional method combined with the inequality techniques some sufficient conditions ensuring the passivity and global exponential stability are derived furthermore when the parameter uncertainties appear in rdnns several criteria for robust passivity and robust global exponential stability are also presented finally a numerical example is provided to illustrate the effectiveness of the proposed criteria

brief on robust stabilization of markovian jump systems with uncertain switching probabilities this brief paper is concerned with the robust stabilization problem for a class of markovian jump linear systems with uncertain switching probabilities the uncertain markovian jump system under consideration involves parameter uncertainties both in the system matrices and in the mode transition rate matrix first a new criterion for testing the robust stability of such systems is established in terms of linear matrix inequalities then a sufficient condition is proposed for the design of robust state feedback controllers a globally convergent algorithm involving convex optimization is also presented to help construct such controllers effectively finally a numerical simulation is used to illustrate the developed theory

treating volumetric inequality constraint in a continuum media with a coupled x fem level set strategy some mechanical problems involve inequality kinematic constraints this study deals with an original approach to handle those difficult problems the inequality constraint implies variational inequality since the area where the constraint is active is a priori unknown the method introduced here is to find the exact constrained area iteratively starting from an initial trial one thanks to numerical tools such as level set and x fem we turn the constrained minimization problem into a shape equilibrium problem

a continuous lagrangian sensitivity equation method for incompressible flow a continuous lagrangian sensitivity equation method clsem is presented as a cost effective alternative to the continuous eulerian sensitivity equation method cesem in the case of shape parameters boundary conditions for the clsem are simpler than those of the cesem however a mapping must be introduced to relate the undeformed and deformed configurations thus making the pdes more complicated we propose the use of pseudo elasticity equations to provide a general framework to generate this mapping for unstructured meshes on complex geometries the methodology is presented in details for the incompressible navier stokes and sensitivity equations in variational form the pdes are solved with an adaptive fem sensitivity data obtained with both approaches for a flow around a naca 4512 are used to obtain estimates of flows around nearby geometries results indicate that the clsem produces significant improvements in terms of both accuracy and cpu time

instantaneous frequency and short term fourier transforms application to piano sounds for more than 30 years and until nowadays development of a system reproducing the functioning of human hearing has remained an aim difficult to reach recent methods for identification of the fundamental frequency of musical sounds obtain good results using information about the temporal evolution of the amplitude and frequency of individual sound partials piano sounds and polyphonic sounds which can have several partials that are closely spaced in the frequency domain have not been extensively tested by these procedures in this paper the instantaneous frequency if as defined by the hilbert transform is used to obtain the frequency variations of piano sounds partials the result implies that for these sounds the if may contain modulations resulting in the separation of an apparent single sinusoid signal into two or more sinusoidal components at various times in the analysis process which makes it impossible to use the temporal evolution of the frequency of partials for the procedure of note identification the separation phenomenon also appears when the short term fourier transform is used and can induce the detection of short lived parasitic spectral peaks that must be taken into account by any note identification procedure based on the use of spectral information

robust stabilization design of nonlinear stochastic partial differential systems fuzzy approach abstract in this paper we address the robust stabilization design problem for nonlinear stochastic partial differential systems nspdss in the presence of random external disturbances and measurement noise in the spatio temporal domain we propose a fuzzy stochastic partial differential system to approximate the nspdss based on fuzzy interpolation approach next we develop a fuzzy stochastic spatial state space model to represent the fuzzy stochastic partial differential system by employing a semi discretization finite difference scheme based on this model we propose a robust fuzzy estimator based stabilization controller to stabilize the nspdss furthermore robust stochastic h stabilization design is suggested to attenuate the effects of random external disturbances and measurement noise in the spatio temporal domain from the area energy point of view the lmi technique is applied to solve the issue of control gains and estimator gains of the controller by using a systematic control design procedure finally a simulation is presented as an example to illustrate the design procedure and to confirm the performance of the proposed robust fuzzy estimator based stabilization design for the nspdss

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

stochastic resonance on weakly paced scale free networks we study the impact of additive gaussian noise and weak periodic forcing on the dynamics of a scale free network of bistable overdamped oscillators the periodic forcing is introduced to a single oscillator and therefore acts as a pacemaker trying to impose its rhythm on the whole ensemble we show that an intermediate intensity of temporally and spatially uncorrelated noise is able to optimally assist the pacemaker in achieving this goal thus providing evidence for stochastic resonance on weakly paced scale free networks because of the inherent degree inhomogeneity of individual oscillators forming the scale free network the placement of the pacemaker within the network is thereby crucial as two extremes we consider separately the introduction of the pacemaker to the oscillator with the highest degree and to one of the oscillators having the lowest degree in both cases the coupling strength plays a crucial role since it determines to what extent the whole network will follow the pacemaker on the expense of a weaker correlation between the pacemaker and the units that are directly linked with the paced oscillator higher coupling strengths facilitate the global outreach of the pacemaker but require higher noise intensities for the optimal response in contrast lower coupling strengths and comparatively low noise intensities localize the optimal response to immediate neighbors of the paced oscillator if the pacemaker is introduced to the main hub the transition between the locally and globally optimal responses is characterized by a double resonance that postulates the existence of an optimal coupling strength for the transmission of weak rhythmic activity across scale free networks we corroborate the importance of the inhomogeneous structure of scale free networks by additionally considering regular networks of oscillators with different degrees of coupling

almost sure exponential stability of stochastic reaction diffusion systems abstract the lyapunov direct method as the most effective measure of studying stability theory for ordinary differential systems and stochastic ordinary differential systems has not been generalized to research concerning stochastic partial differential systems owing to the emptiness of the corresponding ito differential formula the goal of this paper is just employing the lyapunov direct method to investigate the stability of ito stochastic reaction diffusion systems including asymptotical stability in probability and almost sure exponential stability the obtained results extend the conclusions of x x liao x r mao exponential stability and instability of stochastic neural networks stochastic analysis and applications 14 2 1996 165 185 x x liao s z yang s j cheng y l fu stability of general neural networks with reaction diffusion science in china f 44 5 2001 389 395

dynamical behavior of delayed reaction diffusion hopfield neural networks driven by infinite dimensional wiener processes in this paper we focus on the long time behavior of the mild solution to delayed reaction diffusion hopfield neural networks drdhnns driven by infinite dimensional wiener processes we analyze the existence uniqueness and stability of this system under the local lipschitz function by constructing an appropriate lyapunov krasovskii function and utilizing the semigroup theory some easy to test criteria affecting the well posedness and stability of the networks such as infinite dimensional noise and diffusion effect are obtained the criteria can be used as theoretic guidance to stabilize drdhnns in practical applications when infinite dimensional noise is taken into consideration meanwhile considering the fact that the standard brownian motion is a special case of infinite dimensional wiener process we undertake an analysis of the local lipschitz condition which has a wider range than the global lipschitz condition two samples are given to examine the availability of the results in this paper simulations are also given using the matlab

periodic attractor for reactiondiffusion high order hopfield neural networks with time varying delays this paper is concerned with a class of reactiondiffusion high order hopfield neural networks with time varying delays subject to the dirichlet boundary condition in a bounded domain easily verifiable delay independent criteria are established to ensure the existence of periodic mild solutions and the global exponential stability of the periodic mild solutions is also discussed by using the exponential dissipation property of semigroup of operators the obtained results are easy to check and they effectually complement previously known results a numerical example is given to show the effectiveness of theoretical results

shape sensitivity analysis in linear elastic fracture mechanics shape sensitivity analysis of an elastic solid in equilibrium with a known load system applied over its boundary is presented in this work the domain and boundary integral expressions of the first and second order shape derivatives of the total potential energy are established by using an arbitrary change of the domain characterized by a velocity field defined over the initial body configuration in these expressions we recognize free divergence tensors that are denoted in this paper as energy shape change tensors next shape sensitivity analysis is applied to cracked bodies for that purpose a suitable velocity distribution field is adopted to simulate the crack advance of a unit length in a two dimensional body finally the corresponding domain and the equivalent path independent integral expressions of the first and second order potential energy release rate of fracture mechanics are also derived

stabilization for markovian jump systems with partial information on transition probability based on free connection weighting matrices this paper focuses on stability and stabilization for a class of continuous time markovian jump systems with partial information on transition probability the free connection weighting matrix method is proposed to obtain a less conservative stability criterion of markovian jump systems with partly unknown transition probability or completely unknown transition probability as a result a sufficient condition for the state feedback controller design is derived in terms of linear matrix inequalities finally numerical examples are given to illustrate the effectiveness and the merits of the proposed method

brief paper stability and stabilization of markovian jump linear systems with partly unknown transition probabilities in this paper the stability and stabilization problems of a class of continuous time and discrete time markovian jump linear system mjls with partly unknown transition probabilities are investigated the system under consideration is more general which covers the systems with completely known and completely unknown transition probabilities as two special cases the latter is hereby the switched linear systems under arbitrary switching moreover in contrast with the uncertain transition probabilities studied recently the concept of partly unknown transition probabilities proposed in this paper does not require any knowledge of the unknown elements the sufficient conditions for stochastic stability and stabilization of the underlying systems are derived via lmis formulation and the relation between the stability criteria currently obtained for the usual mjls and switched linear systems under arbitrary switching are exposed by the proposed class of hybrid systems two numerical examples are given to show the validity and potential of the developed results

a general methodology for structural shape optimization problems using automatic adaptive remeshing this methodology is based on the use of the adaptive mesh refinement techniques in the context of 2d shape optimization problems a technique for the parametrization of the optimization problem using b splines to define the boundary is first presented then mesh generation using the advancing frontal method the error estimator and the mesh refinement criterion are studied in the context of shape optimization problems in particular the analytical sensitivity analysis of the different items ruling the problem b splines finite element mesh structural behaviour and error estimator is studied in detail

finite time stability and stabilization of ito stochastic systems with markovian switching mode dependent parameter approach this technical note is concerned about the finite time stability and stabilization for ito stochastic systems with markovian switching a mode dependent parameter approach is proposed to give a sufficient condition for finite time stability and its superiority to common parameter approach is analyzed moreover the finite time stabilization is studied and two new sufficient conditions for the existence of state and output feedback controllers are presented in terms of coupled matrix inequalities a n mode algorithm is given for solving the obtained matrix inequalities arising from finite time stability stabilization finally an example is employed to illustrate the effectiveness of our obtained results

stability of markovian jump stochastic parabolic it o equations with generally uncertain transition rates abstract in this paper the stability problem for delayed markovian jump stochastic parabolic it o equations dmjspies subject to generally uncertain transition rates gutrs is investigated via lyapunov krasovskii functional and linear matrix inequality lmi method in the model discussed we suppose that only part of the transition rates of the jumping process are known namely some factors have been already available some elements have been simply known with lower and upper bounds and the rest of elements may have no useful information lastly the applicability and effectiveness of the obtained results are illustrated through an example

stabilization of singular markovian jump systems with generally uncertain transition rates this note is devoted to investigating the stability and stabilization problems for continuous time singular markovian jump systems smjss with generally uncertain transition rates gutrs in this gutr singular model each transition rate can be completely unknown or only its estimate value is known in terms of a set of coupled linear matrix inequalities lmis a sufficient condition is established to ensure the systems to be regular impulse free and stochastically stable moreover the corresponding sufficient condition on the existence of a mode dependent state feedback controller is derived to guarantee the closed loop systems stochastically admissible by applying the lmi technique finally a numerical example is presented to illustrate the effectiveness and efficiency of the proposed method

global asymptotic stability of stochastic bam neural networks with distributed delays and reaction diffusion terms this paper is concerned with global asymptotic stability of a class of reaction diffusion stochastic bi directional associative memory bam neural networks with discrete and distributed delays based on suitable assumptions we apply the linear matrix inequality lmi method to propose some new sufficient stability conditions for reaction diffusion stochastic bam neural networks with discrete and distributed delays the obtained results are easy to check and improve upon the existing stability results an example is also given to demonstrate the effectiveness of the obtained results

exponential stability for stochastic reaction diffusion bam neural networks with time varying and distributed delays abstract in this paper we study the stability for a class of stochastic bidirectional associative memory bam neural networks with reaction diffusion and mixed delays the mixed delays considered in this paper are time varying and distributed delays based on a new lyapunov krasovskii functional and the poincare inequality as well as stochastic analysis theory a set of novel sufficient conditions are obtained to guarantee the stochastically exponential stability of the trivial solution or zero solution the obtained results show that the reaction diffusion term does contribute to the exponentially stabilization of the considered system moreover two numerical examples are given to show the effectiveness of the theoretical results

on global asymptotic stability of recurrent neural networks with time varying delays in this paper by constructing a new lyapunov functional and using m matrix and topological degree tool problem of the global asymptotic stability gas is discussed for a class of recurrent neural networks with time varying delays some simple and new sufficient conditions are obtained ensuring existence uniqueness of the equilibrium point and its gas of the neural networks some previous works are improved in addition this condition does not require the activation functions to be differentiable bounded and monotone nondecreasing and the weight connected matrices to be symmetric the neural network model considered in this paper include the delayed hopfield neural networks bidirectional associative memory networks and delayed cellular neural networks as its special cases

shape sensitivity analysis and the energy momentum tensor for the kinematic and static models of torsion abstract the aim of this paper is to bridge shape sensitivity analysis and configurational mechanics by means of a widespread use of the shape derivative concept this technique will be applied as a systematic procedure to obtain the eshelby s energy momentum tensor associated to the problem under consideration in order to highlight special features of this procedure and without loss of generality we focus our attention in the application of shape sensitivity analysis to the problem of twisted straight bars within the framework of linear elasticity kinematic and static variational formulations as well as the direct method of sensitivity analysis are used to perform shape derivatives of both models integral expressions of first and second order shape derivatives of the total potential energy and the complementary potential energy with respect to an arbitrary transverse cross section shape change are achieved these integral expressions put in evidence the relationship between shape sensitivity analysis and the first and second order eshelby s energy momentum tensors also the null divergence property of these tensors is easily proved by comparing in each case the domain and boundary integral shape derivative arrived at finally an example with a known exact solution corresponding to an elastic bar with elliptical transverse cross section submitted to twist is presented in order to illustrate the usefulness of these tensors to compute the corresponding shape derivatives

an exposition of the material derivative approach for structural shape sensitivity analysis abstract the material derivative approach for structural shape design sensitivity analysis is described in a unified manner using the continuum formulation both the direct differentiation and adjoint methods are derived and computer implementation aspects are discussed the basic purpose of the paper is to present the shape design sensitivity analysis as an application of the material derivative concept of continuum mechanics and the calculus of variation procedures for taking variations of integrals over the variable domains it is also shown that the use of a recently developed variational principle for design sensitivity analysis greatly simplifies derivation of the adjoint method the indicial notation is used and expressions derived by different authors are related to each other a basic understanding of the material derivative approach of shape sensitivity analysis has been gained which can lead to insights for computer implementations of the method

random attractors for stochastic reaction diffusion equations on unbounded domains the existence of a pullback attractor is established for a stochastic reaction diffusion equation on all n dimensional space the nonlinearity is dissipative for large values of the state and the stochastic nature of the equation appears as spatially distributed temporal white noise the reaction diffusion equation is recast as a random dynamical system and asymptotic compactness for this is demonstrated by using uniform a priori estimates for far field values of solutions

a mode decoupling continuum shape sensitivity method for fracture analysis of functionally graded materials in this paper new mode decoupling continuum shape sensitivity method for calculating mixed mode stress intensity factors for a stationary crack in two dimensional linear elastic functionally graded materials with arbitrary geometry is presented the proposed method involves the mode decoupling of deformations the material derivative concept taken from continuum mechanics and direct differentiation the discrete form of the energy release rate is simple and easy to calculate as it only requires multiplication of displacement vectors and stiffness sensitivity matrices by judiciously selecting the velocity field the method only requires displacement response in a sub domain close to the crack tip thus making the method computationally efficient excellent agreement is obtained between stress intensity factors predicted by the proposed method and available reference solutions in the literature therefore mode decoupling shape sensitivity analysis provides an attractive alternative to fracture analysis of cracks in homogeneous and non homogeneous materials

musical fundamental frequency tracking using a pattern recognition method in a recent article j c brown calculation of a constant q spectral transform j acoust soc am 89 425 434 1991 the calculation of a constant q spectral transform that gives a constant pattern in the log frequency domain for sounds with harmonic frequency components has been described this property has been utilized in calculating the cross correlation function of spectra of sounds produced by musical instruments with the ideal pattern which consists of one s at the positions of harmonic frequency components therefore the position of the best approximation to the ideal pattern for the spectra produced by these instruments has been determined and in so doing the fundamental frequency for that sound has been obtained results are presented for scales produced by the piano flute and violin as well as for arpeggios played by a wide variety of instruments

global exponential p stability of stochastic non autonomous takagi sugeno fuzzy cellular neural networks with time varying delays and impulses in this paper we investigate the global exponential p stability of stochastic non autonomous takagi sugeno fuzzy cellular neural networks with time varying delays and impulses by using the property of m matrix we establish a new differential inequality and a new l operator inequality to be effective for non autonomous takagi sugeno fuzzy systems based on the inequalities obtained above sufficient conditions ensuring the global exponential p stability of the considered system are obtained in addition we derive sufficient conditions ensuring the global exponential stability of the corresponding autonomous systems our results improve some early results in the literature one example is given to illustrate the effectiveness of our proposal

impulsive synchronization of reaction diffusion neural networks with mixed delays and its application to image encryption this paper presents a new impulsive synchronization criterion of two identical reaction diffusion neural networks with discrete and unbounded distributed delays the new criterion is established by applying an impulse time dependent lyapunov functional combined with the use of a new type of integral inequality for treating the reaction diffusion terms the impulse time dependent feature of the proposed lyapunov functional can capture more hybrid dynamical behaviors of the impulsive reaction diffusion neural networks than the conventional impulse time independent lyapunov functions functionals while the new integral inequality which is derived from wirtinger s inequality overcomes the conservatism introduced by the integral inequality used in the previous results numerical examples demonstrate the effectiveness of the proposed method later the developed impulsive synchronization method is applied to build a spatiotemporal chaotic cryptosystem that can transmit an encrypted image the experimental results verify that the proposed image encrypting cryptosystem has the advantages of large key space and high security against some traditional attacks

isogeometric shape design sensitivity analysis of stress intensity factors for curved crack problems abstract an isogeometric shape design sensitivity analysis method is developed for the stress intensity factors sifs in curved crack problems in order to obtain an enhanced shape sensitivity of sifs exact higher order geometric information of curvature and normal vector is embedded in the isogeometric shape sensitivity expressions a direct differentiation method is employed for the design sensitivity analysis and the size and orientation of the crack are selected as design variables in the isogeometric approach the nurbs basis functions in cad system are directly utilized in the response analysis which enables a seamless incorporation of exact geometry and higher continuity into the computational framework the precise evaluation of the crack face integral as well as the interaction integral is essential for the computation of the stress intensity factors for the curved crack problems in a mixed mode the cad based exact representation of tangential and normal vectors enables us to exactly define a local coordinate system at the crack tip whose shape dependency naturally leads to configuration design variations that include the change of crack orientation compared with the conventional finite element approach a higher continuity of stress and strain fields are expected in the interaction integral domain the design dependencies of auxiliary field and q function are considered in the design sensitivity formulation reflecting the convection effects due to the non constant design velocity in the interaction integral domain various numerical examples of curved crack problems are presented to verify the developed isogeometric sensitivity analysis method through the comparison with exact and finite element solutions