stochastic resonance in an ensemble of bistable systems under stable distribution noises and nonhomogeneous coupling in this paper stochastic resonance of an ensemble of coupled bistable systems driven by noise having an stable distribution and nonhomogeneous coupling is investigated the stable distribution considered here is characterized by four intrinsic parameters 0 2 is called the stability parameter for describing the asymptotic behavior of stable densities 1 1 is a skewness parameter for measuring asymmetry 0 is a scale parameter for measuring the width of the distribution and is a location parameter for representing the mean value it is demonstrated that the resonant behavior is optimized by an intermediate value of the diversity in coupling strengths we show that the stability parameter and the scale parameter can be well selected to generate resonant effects in response to external signals in addition the interplay between the skewness parameter and the location parameter on the resonance effects is also studied we further show that the asymmetry of a l evy stable distribution resulting from the skewness parameter and the location parameter can enhance the resonance effects both theoretical analysis and simulation are presented to verify the results of this paper

stability analysis and synthesis of nonlinear time delay systems via linear takagi sugeno fuzzy models abstract this paper concerns with the stability analysis and synthesis of nonlinear retarded systems via linear takagi sugeno ts fuzzy model approach first the ts fuzzy models with time delay are present and the stability conditions are derived using lyapunov razumikhin functional approach then a stabilization approach for nonlinear retarded systems through fuzzy state feedback and fuzzy observer based controller is proposed it shows that the analysis results provide an efficient technique for the design of fuzzy controllers sufficient conditions for the existence of fuzzy state feedback gain and fuzzy observer gain of the time delay systems are derived through the numerical solution of a set of coupled linear matrix inequalities

an improvement on delay and its time derivative dependent robust stability of time delayed linear systems with uncertainty in this paper an improvement on the stability result in the above paper by jin hoon see ibid vol 46 2001 is given based on a modified lyapunov function it is shown that our result is much less conservative than that in the paper especially when the size of derivative of the time delay increases for comparison we give two examples

nonlinear feedback design for fixed time stabilization of linear control systems two types of nonlinear control algorithms are presented for uncertain linear plants controllers of the first type are stabilizing polynomial feedbacks that allow to adjust a guaranteed convergence time of system trajectories into a prespecified neighborhood of the origin independently on initial conditions the control design procedure uses block control principles and finite time attractivity properties of polynomial feedbacks controllers of the second type are modifications of the second order sliding mode control algorithms they provide global finite time stability of the closed loop system and allow to adjust a guaranteed settling time independently on initial conditions control algorithms are presented for both single input and multi input systems theoretical results are supported by numerical simulations

robust h sup spl infin filtering for uncertain markovian jump systems with mode dependent time delays this paper considers the problem of robust h sup spl infin filtering for uncertain markovian jump linear systems with time delays which are time varying and depend on the system mode the parameter uncertainties are time varying norm bounded the aim of this problem is to design a markovian jump linear filter that ensures robust exponential mean square stability of the filtering error system and a prescribed l sub 2 induced gain from the noise signals to the estimation error for all admissible uncertainties a sufficient condition for the solvability of this problem is obtained the desired filter can be constructed by solving a set of linear matrix inequalities an illustrative numerical example is provided to demonstrate the effectiveness of the proposed approach

novel robust stability criterion for a class of neutral systems with mixed delays and nonlinear perturbations in this paper a class of neutral systems with mixed delays and nonlinear perturbations is considered a novel robust stability criterion of the system is derived by using lyapunov method the criterion can be easily solved by efficient convex optimization algorithms some numerical examples are given to illustrate our result

finite time synchronization for a class of fuzzy cellular neural networks with time varying coefficients and proportional delays abstract based on the finite time stability theory this paper deals with finite time synchronization for a class of fuzzy cellular neural networks with time varying coefficients and proportional delays using differential inequality techniques and the analysis approach we derive some new and useful sufficient conditions of finite time synchronization for the addressed systems finally an illustrative example with its numerical simulations is given to show the effectiveness of main results

generalized thermostatistics based on deformed exponential and logarithmic functions abstract the equipartition theorem states that inverse temperature equals the log derivative of the density of states this relation can be generalized by introducing a proportionality factor involving an increasing positive function x it is shown that this assumption leads to an equilibrium distribution of the boltzmann gibbs form with the exponential function replaced by a deformed exponential function in this way one obtains a formalism of generalized thermostatistics introduced previously by the author it is shown that tsallis thermostatistics with a slight modification is the most obvious example of this formalism and corresponds with the choice x x q

quadratic stability and stabilization of uncertain linear discrete time systems with state delay abstract this paper deals with the problem of quadratic stability analysis and quadratic stabilization for uncertain linear discrete time systems with state delay the system under consideration involves state time delay and time varying norm bounded parameter uncertainties appearing in all the matrices of the state space model necessary and sufficient conditions for quadratic stability and quadratic stabilization are presented in terms of certain matrix inequalities respectively a robustly stabilizing state feedback controller can be constructed by using the corresponding feasible solution of the matrix inequalities two examples are presented to demonstrate the effectiveness of the proposed approach

brief paper lyapunov function design for finite time convergence analysis twisting controller for second order sliding mode realization a generalization of the zubov method of a lyapunov function design is presented it is based on the characteristic method application and is related to resolving the first order partial differential equation of a special type a successful resolution of this equation guaranties a finite time convergence for the corresponding dynamics given by an ordinary differential equation with a discontinuous right hand side the suggested method is illustrated by its application to the so called twisting controller stability analysis the constructed lyapunov function as well as its level line sections is graphically illustrated

novel robust stability criteria for uncertain systems with time varying delay this paper is concerned with the delay dependent stability and robust stability criteria for linear systems with time varying delay and norm bounded uncertainties through constructing a general form of lyapunov krasovskii functional and using integral inequalities some slack matrices and newly established convex combination condition in the calculation the delay dependent stability criteria are derived in terms of linear matrix inequalities numerical examples are given to illustrate the improvement on the conservatism of the delay bound over some reported results in the literature

self similarity degree of deformed statistical ensembles abstract we consider self similar statistical ensembles with the phase space whose volume is invariant under the deformation that squeezes expands the coordinate and expands squeezes the momentum the related probability distribution function is shown to possess a discrete symmetry with respect to manifold action of the jackson derivative to be a homogeneous function with a self similarity degree q fixed by the condition of invariance under n 1 fold action of the related dilatation operator in slightly deformed phase space we find the homogeneous function is defined with the linear dependence at n 0 whereas the self similarity degree equals the gold mean at n 1 and q n in the limit n dilatation of the homogeneous function is shown to decrease the self similarity degree q at n 0

robust stability criteria for systems with interval time varying delay and nonlinear perturbations this paper considers the robust stability for a class of linear systems with interval time varying delay and nonlinear perturbations a lyapunov krasovskii functional which takes the range information of the time varying delay into account is proposed to analyze the stability a new approach is introduced for estimating the upper bound on the time derivative of the lyapunov krasovskii functional on the basis of the estimation and by utilizing free weighting matrices new delay range dependent stability criteria are established in terms of linear matrix inequalities lmis numerical examples are given to show the effectiveness of the proposed approach

effective temperature of self similar time series analytical and numerical developments abstract within both slightly non extensive statistics and a related numerical model a picture is elaborated to treat self similar time series as a thermodynamic system thermodynamic type characteristics relevant to temperature pressure entropy internal and free energies are introduced and tested predictability conditions of time series analysis are discussed on the basis of van der waals model maximal magnitude for time interval and minimal resolution scale of the value under consideration are found and analyzed in details the statistics developed is shown to be governed by effective temperature being an exponential measure of the fractal dimension of the time series testing of the analytical consideration is based on numerical scheme of non extensive random walk a statistical scheme is introduced to present the numerical model as a grand canonical ensemble for which entropy and internal energy are calculated as functions of particle number effective temperature is found numerically to show that its value is reduced to averaged energy per one degree of freedom

a continuous time observer which converges in finite time it is shown that a continuous time observer which comprises two standard nth order observers and a delay d can observe the state of an nth order linear system in finite time d exactly in particular almost any convergence time d can be assigned independent of the observer eigenvalues

stability of fuzzy control systems with bounded uncertain delays global exponential stability of fuzzy control systems with delays is studied these delays in the fuzzy control systems are assumed to be any uncertain bounded continuous functions stability of systems with uncertain delays is interesting since in practical applications it is not easy to know the delays exactly conditions for global exponential stability of free fuzzy systems with uncertain delays are derived criteria for design of nonlinear fuzzy controllers to feedback control the stability of global nonlinear fuzzy systems are given theorems are proved via the method of functional differential inequalities analysis

on exponential stability results for fuzzy impulsive neural networks complex nonlinear systems can be represented to a set of linear sub models by using fuzzy sets and fuzzy reasoning via ordinary takagi sugeno ts fuzzy models in this paper the exponential stability of ts fuzzy neural networks with impulsive effect and time varying delays is investigated the model for fuzzy impulsive neural networks with time varying delays is first established as a modified ts fuzzy model in which the consequent parts are composed of a set of impulsive neural networks with time varying delays secondly the exponential stability for fuzzy impulsive neural networks is presented by utilizing the lyapunov krasovskii functional and the linear matrix inequality lmi approach in addition two numerical examples are provided to illustrate the applicability of the result using lmi control toolbox in matlab

output feedback robust h sup spl infin control of uncertain fuzzy dynamic systems with time varying delay this paper presents an output feedback robust h sup spl infin control problem for a class of uncertain fuzzy dynamic systems with time varying delayed state the takagi sugeno fuzzy model is employed to represent an uncertain nonlinear systems with time varying delayed state using a single quadratic lyapunov function the globally exponential stability and disturbance attenuation of the closed loop fuzzy control system are discussed sufficient conditions for the existence of robust h sup spl infin controllers are given in terms of matrix inequalities constructive algorithm for design of robust h sup spl infin controller is also developed the resulting controller is nonlinear and automatically tuned based on fuzzy operation

robust asymptotic stability of uncertain fuzzy bam neural networks with time varying delays via ordinary takagi sugeno ts fuzzy models complex nonlinear systems can be represented to a set of linear sub models by using fuzzy sets and fuzzy reasoning in this paper the global asymptotic stability problem of ts fuzzy bi directional associative memories bam neural networks with time varying delays and parameter uncertainties is considered first the model of ts fuzzy bam neural networks with time varying delays and parameter uncertainties is established as a modified ts fuzzy model in which the consequent parts are composed of a set of bam neural networks with time varying delays secondly the globally robust asymptotically stable condition is presented in terms of linear matrix inequalities which can be easily solved by some standard numerical packages two numerical examples are also given to validate the theoretical results

existence and global attractivity of almost periodic solutions for neural field with time delay in this paper the problem of existence and attractivity of almost periodic solutions for delayed neural field dnf with variable coefficients is discussed first the model of dnf is established as a modified neural field model secondly by combining the theory of the exponential dichotomy employing banach fixed point theory and using differential inequality technique some conditions for the the existence and attractivity of almost periodic solutions for the dnf are proposed

solutions of n simplex equation from solutions of braid group representation it is shown that a kind of solution of the n simplex equation can be obtained from representations of the braid group the symmetries in its solution space are also discussed

tsallis entropy maximization procedure revisited abstract the proper way of averaging is an important question with regards to tsallis thermostatistics three different procedures have been thus far employed in the pertinent literature the third one i e the tsallis mendes plastino tmp physica a 261 1998 534 normalization procedure exhibits clear advantages with respect to earlier ones in this work we advance a distinct from the tmp one way of handling the lagrange multipliers involved in the extremization process that leads to tsallis statistical operator it is seen that the new approach considerably simplifies the pertinent analysis without losing the beautiful properties of the tsallis mendes plastino formalism

new results on stability of discrete time systems with time varying state delay this note is concerned with the stability analysis of discrete time systems with time varying state delay by defining new lyapunov functions and by making use of novel techniques to achieve delay dependence several new conditions are obtained for the asymptotic stability of these systems the merit of the proposed conditions lies in their less conservativeness which is achieved by circumventing the utilization of some bounding inequalities for cross products between two vectors and by paying careful attention to the subtle difference between the terms sigmam k dk k 1 middot and sigma m k dm k 1 middot which is largely ignored in the existing literature these conditions are shown via several examples to be much less conservative than some existing result

design of state estimator for bam fuzzy cellular neural networks with leakage and unbounded distributed delays in this paper the state estimation problem is studied for the bidirectional associative memory bam fuzzy cellular neural networks fcnns with delays where the delays include leakage and unbounded distributed delays the problem addressed is to estimate the neuron states through available output measurements such that for all admissible leakage and unbounded distributed delays the dynamics of the estimation error is globally asymptotically stable a delay dependent linear matrix inequality lmi criterion for the existence of the estimator is proposed by using the lyapunovkrasovskii functional method in addition the unknown gain matrix is determined by solving a delay dependent lmi finally numerical examples and simulations are provided to illustrate the effectiveness of the theoretical results

delay dependent stability analysis for a class of dynamical systems with leakage delay and nonlinear perturbations this paper studies the stability problem for a class of dynamical systems with leakage delay and nonlinear perturbations based on linear matrix inequality lmi approach some sufficient conditions which are dependent on the leakage delay are derived to ensure the global asymptotic stability by using lyapunov krasovskii functional method and free weighting matrix technique two examples and their simulations are given to show the effectiveness and advantage of the present results

finite time h asynchronous state estimation for discrete time fuzzy markov jump neural networks with uncertain measurements abstract this paper is concerned with the problem of the h asynchronous state estimation for fuzzy markov jump neural networks fmjnns with uncertain measurements over a finite time interval in terms of a bernoulli distributed white sequence the phenomenon of the randomly occurring uncertainties in the output equation is represented by exploiting a random variable with known occurrence probabilities the main focus of this paper is to present a state estimator such that the resulting error system is finite time bounded and satisfies an h performance requirement then by employing the stochastic analysis technique sufficient conditions are provided to ensure that the state estimator is designed by means of solving a convex optimization problem an example is finally given to explain the effectiveness and potentiality of the proposed design method

nonconcave entropies in multifractals and the thermodynamic formalism we discuss a subtlety involved in the calculation of multifractal spectra when these are expressed as legendre fenchel transforms of functions analogous to free energy functions we show that the legendre fenchel transform of a free energy function yields the correct multifractal spectrum only when the latter is wholly concave if the spectrum has no definite concavity then the transform yields the concave envelope of the spectrum rather than the spectrum itself some mathematical and physical examples are given to illustrate this result which lies at the root of the nonequivalence of the microcanonical and canonical ensembles on a more positive note we also show that the impossibility of expressing nonconcave multifractal spectra through legendre fenchel transforms of free energies can be circumvented with the help of a generalized free energy function which relates to a recently introduced generalized canonical ensemble analogies with the calculation of rate functions in large deviation theory are finally discussed

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 analysis for discrete time stochastic markovian jump neural networks with mixed time delays in this paper passivity analysis is conducted for discrete time stochastic neural networks with both markovian jumping parameters and mixed time delays the mixed time delays consist of both discrete and distributed delays the markov chain in the underlying neural networks is finite piecewise homogeneous by introducing a lyapunov functional that accounts for the mixed time delays a delay dependent passivity condition is derived in terms of the linear matrix inequality approach the case of markov chain with partially unknown transition probabilities is also considered all the results presented depend upon not only discrete delay but also distributed delay a numerical example is included to demonstrate the effectiveness of the proposed methods

stabilization for markovian jump nonlinear systems with partly unknown transition probabilities via fuzzy control abstract this paper is concerned with the stability and stabilization problems for a class of nonlinear systems with markovian jump parameters the takagi sugeno t s fuzzy model is employed to represent the markovian jump nonlinear systems with partly unknown transition probabilities in contrast with the certain or uncertain transition probabilities investigated recently the concept of partly unknown transition probabilities does not need any knowledge of the unknown elements some sufficient conditions for stochastic stability and stabilization conditions with a mode dependent fuzzy controller are derived for the markovian jump fuzzy systems in terms of linear matrix inequalities lmis a numerical example is provided to illustrate the design developed in this paper

compensatory neurofuzzy systems with fast learning algorithms in this paper a new adaptive fuzzy reasoning method using compensatory fuzzy operators is proposed to make a fuzzy logic system more adaptive and more effective such a compensatory fuzzy logic system is proved to be a universal approximator the compensatory neural fuzzy networks built by both control oriented fuzzy neurons and decision oriented fuzzy neurons cannot only adaptively adjust fuzzy membership functions but also dynamically optimize the adaptive fuzzy reasoning by using a compensatory learning algorithm the simulation results of a cart pole balancing system and nonlinear system modeling have shown that 1 the compensatory neurofuzzy system can effectively learn commonly used fuzzy if then rules from either well defined initial data or ill defined data 2 the convergence speed of the compensatory learning algorithm is faster than that of the conventional backpropagation algorithm and 3 the efficiency of the compensatory learning algorithm can be improved by choosing an appropriate compensatory degree

multifractal spectrum of phase space related to generalized thermostatistics abstract we consider a self similar phase space with specific fractal dimension d being distributed with spectrum function f d related thermostatistics is shown to be governed by the tsallis formalism of the non extensive statistics where the non additivity parameter equals to q 1 q 1 and the multifractal function q q d q f d q is the specific heat determined with multifractal parameter q 1 at that the equipartition law is shown to take place optimization of the multifractal spectrum function f d arrives at the relation between the statistical weight and the system complexity it is shown that the statistical weight exponent q can be modeled by hyperbolic tangent deformed in accordance with both tsallis and kaniadakis exponential functions to describe arbitrary multifractal phase space explicitly the spectrum function f d is proved to increase monotonically from minimum value f 1 at d 0 to maximum one f 1 at d 1 at the same time the number of monofractals increases with the growth of the phase space volume at small dimensions d and falls down in the limit d 1

exponential stability of delayed bi directional associative memory networks some sufficient conditions are derived for the global exponential stability in delayed bi directional associative memory bam networks by constructing suitable lyapunov functional and the inequality 2ab

fuzzy hyperbolic neural network with time varying delays in this paper the formula of fuzzy basis functions with time varying delays dfbf is firstly given based on the dfbf a novel fuzzy hyperbolic neural network with time varying delays dfhnn and its approximation properties are presented respectively by constructing an appropriate lyapunov krasovskii functional the stability of dfhnn is discussed and some new criteria concerning the global exponential stability of dfhnn are proposed finally three numerical examples are given to demonstrate the effectiveness of the obtained results

synchronization of markovian coupled neural networks with nonidentical node delays and random coupling strengths in this paper a general model of coupled neural networks with markovian jumping and random coupling strengths is introduced in the process of evolution the proposed model switches from one mode to another according to a markovian chain and all the modes have different constant time delays the coupling strengths are characterized by mutually independent random variables when compared with most of existing dynamical network models which share common time delay for all modes and have constant coupling strengths our model is more practical because different chaotic neural network models can have different time delays and coupling strength of complex networks may randomly vary around a constant due to environmental and artificial factors by designing a novel lyapunov functional and using some inequalities and the properties of random variables we derive several new sufficient synchronization criteria formulated by linear matrix inequalities the obtained criteria depend on mode delays and mathematical expectations and variances of the random coupling strengths as well numerical examples are given to demonstrate the effectiveness of the theoretical results meanwhile right continuous markovian chain is also presented

weight conservation condition and structure of the braid group representation a weight conservation condition for the s matrix of the braid group representation from which non vanishing elements of the s matrix can be determined is introduced a method of weight lattice analysis of representations of lie algebra is suggested and used to give structures of braid group representations in various cases this makes it feasible for braid group representations to be obtained by solving the spectral parameter independent yang baxter equation directly which leads to several new braid group representations

brief paper exponential stability of singular systems with multiple time varying delays this paper deals with the class of continuous time singular linear systems with multiple time varying delays in a range the global exponential stability problem of this class of systems is addressed delay range dependent sufficient conditions such that the system is regular impulse free and a stable are developed in the linear matrix inequality lmi setting moreover an estimate of the convergence rate of such stable systems is presented a numerical example is employed to show the usefulness of the proposed results

delay dependent robust stabilization of uncertain state delayed systems this paper concerns a problem of robust stabilization of uncertain state delayed systems a new delay dependent stabilization condition using a memoryless controller is formulated in terms of matrix inequalities an algorithm involving convex optimization is proposed to design a controller guaranteeing a suboptimal maximal delay such that the system can be stabilized for all admissible uncertainties

fixed time synchronization of complex networks with impulsive effects via nonchattering control dealing with impulsive effects is one of the most challenging problems in the field of fixed time control in this paper we solve this challenging problem by considering fixed time synchronization of complex networks cns with impulsive effects by designing a new lyapunov function and constructing comparison systems a sufficient condition formulated by matrix inequalities is given to ensure that all the dynamical subsystems in the cns are synchronized with an isolated system in a settling time which is independent of the initial values of both the cns and the isolated system then by partitioning impulse interval and using the convex combination technique sufficient conditions in terms of linear matrix inequalities are provided our synchronization criteria unify synchronizing and desynchronizing impulses compared with the existing controllers for fixed time and finite time techniques the designed controller is continuous and does not include any sign function and hence the chattering phenomenon in most of the existing results is overcome an optimal algorithm is proposed for the estimation of the settling time numerical examples are given to show the effectiveness of our new results

novel delay dependent master slave synchronization criteria of chaotic lur e systems with time varying delay feedback control this paper is concerned with the issue of master slave synchronization for chaotic lur e systems clss with time varying delay feedback control a novel integral inequality is developed by employing two adjustable parameters which encompasses the celebrated wirtinger s integral inequality and jensen s inequality as two special cases by constructing an augmented lyapunov krasovskii functional lkf taking fully the information time varying delay range into account less conservative delay dependent synchronization criteria are established in the form of linear matrix inequalities lims besides the desired controller gain can be achieved by introducing new nonlinear function conditions which have not been proposed so far finally a numerical example of typical chua s circuit is presented to show the improvements over the existing criteria and the effectiveness of the design approach

analysis and synthesis of nonlinear time delay systems via fuzzy control approach takagi sugeno ts fuzzy models 1985 1992 can provide an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear input output i o submodels in this paper the ts fuzzy model approach is extended to the stability analysis and control design for both continuous and discrete time nonlinear systems with time delay the ts fuzzy models with time delay are presented and the stability conditions are derived using lyapunov krasovskii approach we also present a stabilization approach for nonlinear time delay systems through fuzzy state feedback and fuzzy observer based controller sufficient conditions for the existence of fuzzy state feedback gain and fuzzy observer gain are derived through the numerical solution of a set of coupled linear matrix inequalities an illustrative example based on the cstr model is given to design a fuzzy controller

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

technical communique delay range dependent stability for systems with time varying delay this paper is concerned with the stability analysis for systems with time varying delay in a range an appropriate type of lyapunov functionals is proposed to investigate the delay range dependent stability problem the present results may improve the existing ones due to a method to estimate the upper bound of the derivative of lyapunov functional without ignoring some useful terms and the introduction of additional terms into the proposed lyapunov functional which take into account the range of delay numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method

robust stability of uncertain fuzzy bam neural networks of neutral type with markovian jumping parameters and impulses abstract in this paper the problem of neutral type impulsive bidirectional associative memory neural networks nibamnns with time delays are first established by a takagi sugeno t s fuzzy model in which the consequent parts are composed of a set of nibamnns with interval delays and markovian jumping parameters mjps sufficient conditions to check the robust exponential stability of the derived model are based on the lyapunov krasovskii functionals lkfs containing some novel triple integral terms lyapunov stability theory and employing the free weighting matrix method the delay dependent stability conditions are established in terms of linear matrix inequalities lmis which can be very efficiently solved using matlab lmi control toolbox finally numerical examples and remarks are given to illustrate the effectiveness and usefulness of the derived results

fixed time synchronization of markovian jump fuzzy cellular neural networks with stochastic disturbance and time varying delays abstract this paper mainly studies the fixed time synchronization of markovian jump fuzzy cellular neural networks with stochastic perturbations and time varying delays in the leakage term by designing delay dependent controllers with or without fuzzy terms constructing a suitable stochastic lyapunov functional and using matrix analysis techniques this paper derives some novel and useful sufficient conditions to guarantee the fixed time synchronization of the addressed drive response systems and the conditions are delay dependent which has less conservative results the finite time is also independent of the initial states finally numerical examples are given to illustrate the effectiveness of the proposed main results

non linear kinetics underlying generalized statistics abstract the purpose of the present effort is threefold firstly it is shown that there exists a principle that we call kinetical interaction principle kip underlying the non linear kinetics in particle systems independently on the picture kramers boltzmann used to describe their time evolution secondly the kip imposes the form of the generalized entropy associated to the system and permits to obtain the particle statistical distribution both as stationary solution of the non linear evolution equation and as the state which maximizes the generalized entropy thirdly the kip allows on one hand to treat all the classical or quantum statistical distributions already known in the literature in a unifying scheme and on the other hand suggests how we can introduce naturally new distributions finally as a working example of the approach to the non linear kinetics here presented a new non extensive statistics is constructed and studied starting from a one parameter deformation of the exponential function holding the relation f x f x 1

representations of a braid group with transpose symmetry and the related link invariants under a weight conservation condition when q is not a root of unity yang baxter relations are solved without the assumption that the upper left triangle of each sub block of the s matrix of the braid group representation bgr vanishes a general form of bgr associated with bn cn and dn is obtained and shown to construct link invariants the many to one correspondence between bgrs and link invariants is given

further improvement of free weighting matrices technique for systems with time varying delay a novel method is proposed in this note for stability analysis of systems with a time varying delay appropriate lyapunov functional and augmented lyapunov functional are introduced to establish some improved delay dependent stability criteria less conservative results are obtained by considering the additional useful terms which are ignored in previous methods when estimating the upper bound of the derivative of lyapunov functionals and introducing the new free weighting matrices the resulting criteria are extended to the stability analysis for uncertain systems with time varying structured uncertainties and polytopic type uncertainties numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method

robust exponential stability of uncertain fuzzy cohen grossberg neural networks with time varying delays in this paper the takagi sugeno t s fuzzy model representation is extended to the stability analysis for uncertain cohen grossberg neural networks cgnns with time varying delays a novel linear matrix inequality lmi based stability criterion is obtained by using lyapunov functional theory to guarantee the exponential stability of uncertain cgnns with time varying delays which are represented by t s fuzzy models finally the proposed stability conditions are demonstrated with numerical examples

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

global exponential convergence of fuzzy complex valued neural networks with time varying delays and impulsive effects abstract in this paper the global exponential convergence of t s fuzzy complex valued neural networks with time varying delays and impulsive effects is discussed by employing lyapunov functional method and matrix inequality technique we analyze a type of activation functions with lipschitz function and sufficient conditions in terms of complex valued linear matrix inequality are obtained to ensure the global exponential convergence moreover the framework of the exponential convergence ball in the state space of the considered neural networks and the exponential convergence rate index are also given out here the existence and uniqueness of the equilibrium points need not be considered and the results improve existing results on the lyapunov exponential stability as special cases finally one numerical example with simulations is given to illustrate the effectiveness of our theoretical results

exponential stability and periodic oscillatory solution in bam networks with delays both exponential stability and periodic oscillatory solution of bidirectional associative memory bam networks with axonal signal transmission delays are considered by constructing suitable lyapunov functional and some analysis techniques some simple sufficient conditions are given ensuring the global exponential stability and the existence of periodic oscillatory solutions of bam with delays these conditions are presented in terms of system parameters and have important leading significance in the design and applications of globally exponentially stable and periodic oscillatory neural circuits for bam with delays in addition two examples are given to illustrate the results

existence and global exponential stability of equilibrium for discrete time fuzzy bam neural networks with variable delays and impulses in this paper we study a class of discrete time fuzzy bam neural networks with variable delays and impulses based on m matrix theory and analytic methods some sufficient conditions are established for the existence and global exponential stability of a unique equilibrium moreover the exponential convergence rate index is estimated a numerical example is given to show the effectiveness of the obtained results in particular the simulation figures establish that fuzzy systems do have more advantages than non fuzzy systems

delay dependent robust stability for uncertain stochastic fuzzy hopfield neural networks with time varying delays takagi sugeno ts fuzzy models are often used to represent complex nonlinear systems by means of fuzzy sets and fuzzy reasoning applied to a set of linear sub models in this paper the global robust stability problem of ts fuzzy hopfield neural networks with parameter uncertainties and stochastic perturbations is investigated based on the lyapunov method and stochastic analysis approaches the delay dependent stability criterion is derived in terms of linear matrix inequalities lmis which can be solved efficiently by using existing lmi optimization techniques a simulation example is provided to illustrate the effectiveness of the developed method

lagrange exponential stability for fuzzy cohen grossberg neural networks with time varying delays this paper focuses on the globally exponential stability in lagrange sense for takagi sugeno t s fuzzy cohen grossberg neural networks with time varying delays by employing lyapunov method and delay inequality technique we analyze two different types of activation functions which include both lipschitz function and general activation functions several easily verifiable sufficient criteria about linear matrix inequality form are obtained to guarantee the lagrange exponential stability of cohen grossberg neural networks with time varying delays which are represented by t s fuzzy models meanwhile the estimations of the globally exponentially attractive sets are given here the existence and uniqueness of the equilibrium points need not be considered finally two numerical examples with simulations are given to illustrate the effectiveness of the theoretical results

a two directional arnoldi process and its application to parametric model order reduction we consider a two directional krylov subspace k k a j b j where besides the dimensionality k of the subspace increases the matrix a j and vector b j which induce the subspace may also augment specifically we consider the case where the matrix a j and the vector b j are augmented by block triangular bordering we present a two directional arnoldi process to efficiently generate a sequence of orthonormal bases q k j of the krylov subspaces the concept of a two directional krylov subspace and an arnoldi process is triggered by the need of a multiparameter moment matching based model order reduction technique for parameterized linear dynamical systems numerical examples illustrate computational efficiency and flexibility of the proposed two directional arnoldi process

mixed h infinity and passive filtering for discrete fuzzy neural networks with stochastic jumps and time delays in this brief the problems of the mixed h infinity and passivity performance analysis and design are investigated for discrete time delay neural networks with markovian jump parameters represented by takagi sugeno fuzzy model the main purpose of this brief is to design a filter to guarantee that the augmented markovian jump fuzzy neural networks are stable in mean square sense and satisfy a prescribed passivity performance index by employing the lyapunov method and the stochastic analysis technique applying the matrix decomposition techniques sufficient conditions are provided for the solvability of the problems which can be formulated in terms of linear matrix inequalities a numerical example is also presented to illustrate the effectiveness of the proposed techniques

synchronization criteria for coupled neural networks with interval time varying delays and leakage delay abstract this paper considers the synchronization problem for coupled neural networks with interval time varying delays and leakage delay by construction of a suitable lyapunov krasovskii s functional and utilization of finsler s lemma novel delay dependent criteria for the synchronization of the networks are established in terms of linear matrix inequalities lmis which can be easily solved by various effective optimization algorithms two numerical examples are given to illustrate the effectiveness of the proposed methods

the role of constraints within generalized nonextensive statistics the gibbs jaynes path for introducing statistical mechanics is based on the adoption of a specific entropic form sand of physically appropriate constraints for instance for the usual canonical ensemble one adopts i ii ipi 1 and iii ei eigenvalues of the hamiltonian u1 internal energy equilibrium consists in optimizing s1 with regard to pi in the presence of constraints ii and iii within the recently introduced nonextensive statistics i is generalized into sq k 1 ipiq q 1 q 1 reproduces s1 ii is maintained and iii is generalized in a manner which might involve piq in the present effort we analyze the consequences of some special choices for iii and their formal and practical implications for the various physical systems that have been studied in the literature to illustrate some mathematically relevant points we calculate the specific heat respectively associated with a nondegenerate two level system as well as with the classical and quantum harmonic oscillators

substitution systems and nonextensive statistics abstract substitution systems evolve in time by generating sequences of symbols from a finite alphabet at a certain iteration step the existing symbols are systematically replaced by blocks of n k symbols also within the alphabet with n k a natural number being the length of the k th block of the substitution the dynamics of these systems leads naturally to fractals and self similarity by using b calculus garcia morales 2012 universal maps for deterministic substitution systems both of constant and non constant length are formulated in 1d it is then shown how these systems can be put in direct correspondence with tsallis entropy a second law of thermodynamics is also proved for these systems in the asymptotic limit of large words