new criteria of passivity analysis for fuzzy time delay systems with parameter uncertainties this paper investigates the passivity problem for a class of uncertain stochastic fuzzy nonlinear systems with mixed delays and nonlinear noise disturbances by employing an improved free weighting matrix approach the fuzzy system is based on the takagi sugeno model that is often used to represent the complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning to reflect more realistic dynamical behaviors of the system the parameter uncertainties the stochastic disturbances and nonlinearities are considered where the parameter uncertainties enter into all the system matrices the stochastic disturbances are given in the form of a brownian motion the mixed delays comprise both discrete and distributed time varying delays by taking the relationship among the time delays their lower and upper bounds into account some less conservative linear matrix inequality based delay dependent passivity criteria are obtained without ignoring any useful terms in the derivative of lyapunov functional finally numerical examples are given to demonstrate the effectiveness and merits of the proposed methods

on conditional and intrinsic autoregressions summary gaussian conditional autoregressions have been widely used in spatial statistics and bayesian image analysis where they are intended to describe interactions between random variables at fixed sites in euclidean space the main appeal of these distributions is in the markovian interpretation of their full conditionals intrinsic autoregressions are limiting forms that retain the markov property despite being improper they can have advantages over the standard autoregressions both conceptually and in practice for example they often avoid difficulties in parameter estimation without apparent loss or exhibit appealing invariances as in texture analysis however on small arrays and in nonlattice applications both forms of autoregression can lead to undesirable second order characteristics either in the variables themselves or in contrasts among them this paper discusses standard and intrinsic autoregressions and describes how the problems that arise can be alleviated using dempster s 1972 algorithm or an appropriate modification the approach represents a partial synthesis of standard geostatistical and gaussian markov random field formulations some nonspatial applications are also mentioned

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

an optimal fault detection approach for piecewise affine systems via diagnostic observers abstract in this paper the design issues of diagnostic observer based fault detection fd for piecewise affine systems are investigated to be specific the diagnostic observer based fd approaches are developed to satisfy the specified disturbance attenuation and optimize the fault detectability at the same time considering the fact that the measurements are generally corrupted with noises or disturbances the proposed approaches are mainly dedicated to the case that the process and its fd system are non synchronous in transition from one region to another moreover aiming at improving the fd performance a mode observer is integrated to relax the design condition for the residual generator an example is given in the end to show the effectiveness of the proposed approaches

subsmooth semi infinite and infinite optimization problems we first consider subsmoothness for a function family and provide formulas of the subdifferential of the pointwise supremum of a family of subsmooth functions next we consider subsmooth infinite and semi infinite optimization problems in particular we provide several dual and primal characterizations for a point to be a sharp minimum or a weak sharp minimum for such optimization problems

observer based h control of discrete time delay systems with random communication packet losses and multiplicative noises this paper investigates the observer based h control problem for a class of discrete time mixed delay systems with random communication packet losses and multiplicative noises where the mixed delays comprise both discrete and distributed time varying delays the random packet losses are described by a bernoulli distributed white sequence that obeys a conditional probability distribution and the multiplicative disturbances are in the form of a scalar gaussian white noise with unit variance in the presence of mixed delays random packet losses and multiplicative noises sufficient conditions for the existence of an observer based feedback controller are derived such that the closed loop control system is asymptotically mean square stable and preserves a guaranteed h performance then a linear matrix inequality lmi approach for designing such an observer based h controller is presented finally a numerical example is provided to illustrate the effectiveness of the developed theoretical results

an h likelihood method for spatial mixed linear models based on intrinsic auto regressions summary we consider sparse spatial mixed linear models particularly those described by besag and higdon and develop an h likelihood method for their statistical inference the method proposed allows for singular precision matrices as it produces estimates that coincide with those from the residual maximum likelihood based on appropriate differencing of the data and has a novel approach to estimating precision parameters by a gamma linear model furthermore we generalize the h likelihood method to include continuum spatial variations by making explicit use of scaling limit connections between gaussian intrinsic markov random fields on regular arrays and the de wijs process keeping various applications of spatial mixed linear models in mind we devise a novel sparse conjugate gradient algorithm that allows us to achieve fast matrix free statistical computations we provide two applications the first is an extensive analysis of an agricultural variety trial that brings forward various new aspects of nearest neighbour adjustment such as effects on statistical analyses to changes of scale and use of implicit continuum spatial formulation the second application concerns an analysis of a large cotton field which gives a focus to matrix free computations the paper closes with some further considerations such as applications to irregularly spaced data use of the parametric bootstrap and some generalizations to the gaussian matern mixed effect models

statistical analysis of field experiments using neighbouring plots the paper describes and provides examples of four different applications of the use of neighbouring plot values in the analysis of agricultural field experiments the topics include the use of check plots to control environmental variation in large unreplicated variety trials spatial models based on first differences to accommodate fertility effects in trials that have some degree of replication adjustment for interplot competition using a simultaneous equations formulation and the analysis of trials in which plot values are affected by the particular treatments on neighbouring plots

not all possibly random sequences are created equal the need to assess the randomness of a single sequence especially a finite sequence is ubiquitous yet is unaddressed by axiomatic probability theory here we assess randomness via approximate entropy apen a computable measure of sequential irregularity applicable to single sequences of both even very short finite and infinite length we indicate the novelty and facility of the multidimensional viewpoint taken by apen in contrast to classical measures furthermore and notably for finite length finite state sequences one can identify maximally irregular sequences and then apply apen to quantify the extent to which given sequences differ from maximal irregularity via a set of deficit defm functions the utility of these defm functions which we show allows one to considerably refine the notions of probabilistic independence and normality is featured in several studies including i digits of e 2 and 3 both in base 2 and in base 10 and ii sequences given by fractional parts of multiples of irrationals we prove companion analytic results which also feature in a discussion of the role and validity of the almost sure properties from axiomatic probability theory insofar as they apply to specified sequences and sets of sequences in the physical world we conclude by relating the present results and perspective to both previous and subsequent studies

robust passivity and passification of stochastic fuzzy time delay systems in this paper the passivity and passification problems are investigated for a class of uncertain stochastic fuzzy systems with time varying delays the fuzzy system is based on the takagi sugeno t s model that is often used to represent the complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning to reflect more realistic dynamical behaviors of the system both the parameter uncertainties and the stochastic disturbances are considered where the parameter uncertainties enter into all the system matrices and the stochastic disturbances are given in the form of a brownian motion we first propose the definition of robust passivity in the sense of expectation then by utilizing the lyapunov functional method the ito differential rule and the matrix analysis techniques we establish several sufficient criteria such that for all admissible parameter uncertainties and stochastic disturbances the closed loop stochastic fuzzy time delay system is robustly passive in the sense of expectation the derived criteria which are either delay independent or delay dependent are expressed in terms of linear matrix inequalities lmis that can be easily checked by using the standard numerical software illustrative examples are presented to demonstrate the effectiveness and usefulness of the proposed results

reliable state feedback control of t s fuzzy systems with sensor faults this paper is concerned with reliable state feedback control synthesis for takagi and sugeno t s fuzzy systems with sensor multiplicative faults by considering the influence of sensor faults on both the system states and premise variables of fuzzy controllers a class of new convex reliable stabilization conditions are proposed for t s fuzzy systems using the properties of fuzzy product inference engines furthermore the obtained result is extended to the h infty reliable control case the resulting controllers are reliable in that they provide guaranteed asymptotic stability and h infty performance when all sensors are operational as well as when some sensor experiences failures different from the proposed approach the influence of sensor faults on premise variables is not considered in the existing results then it might not guarantee the stability and control performance for t s fuzzy systems with premise variables dependent on the system states a numerical example is given to illustrate the effectiveness of the proposed method

on finite convergence of proximal point algorithms for variational inequalities in this paper we first characterize finite convergence of an arbitrary iterative algorithm for solving the variational inequality problem vip where the finite convergence means that the algorithm can find an exact solution of the problem in a finite number of iterations by using this result we obtain that the well known proximal point algorithm possesses finite convergence if the solution set of vip is weakly sharp as an extension we show finite convergence of the inertial proximal method for solving the general variational inequality problem under the condition of weak g sharpness

weak sharp minima for set valued vector variational inequalities with an application abstract in this paper the notion of weak sharp minima is employed to the investigation of set valued vector variational inequalities the gap function t for set valued strong vector variational inequalities for short svvi is proved to be less than the gap function t for set valued weak vector variational inequalities for short wvvi under certain conditions which implies that the solution set of svvi is equivalent to the solution set of wvvi moreover it is shown that weak sharp minima for the solution sets of svvi and wvvi hold for min 1 i n p t i and for gap functions t and t under the assumption of strong pseudomonotonicity where p t i is a gap function for i th component of svvi and wvvi as an application the weak pareto solution set of vector optimization problems for short vop is proved to be weak sharp minimum for min 1 i n p g i when each component g i of objective function is strongly convex

stability analysis of piecewise discrete time linear systems presents a stability analysis method for piecewise discrete time linear systems based on a piecewise smooth lyapunov function it is shown that the stability of the system can be established if a piecewise lyapunov function can be constructed and moreover the function can be obtained by solving a set of linear matrix inequalities lmis that is numerically feasible with commercially available software

weak sharp minima in mathematical programming the notion of a sharp or strongly unique minimum is extended to include the possibility of a nonunique solution set these minima will be called weak sharp minima conditions necessary for the solution set of a minimization problem to be a set of weak sharp minima are developed in both the unconstrained and constrained cases these conditions are also shown to be sufficient under the appropriate convexity hypotheses the existence of weak sharp minima is characterized in the cases of linear and quadratic convex programming and for the linear complementarity problem in particular a result of mangasarian and meyer is reproduced that shows that the solution set of a linear program is always a set of weak sharp minima whenever it is nonempty consequences for the convergence theory of algorithms are also examined especially conditions yielding finite termination

technical communique reliable h control for discrete time piecewise linear systems with infinite distributed delays in this paper the reliable h control problem is investigated for discrete time piecewise linear systems with time delays and actuator failures the time delays are assumed to be infinitely distributed in the discrete time domain and the possible failure of each actuator is described by a variable varying in a given interval the aim of the addressed reliable h control problem is to design a controller such that for the admissible infinite distributed delays and possible actuator failures the closed loop system is exponentially stable with a given disturbance attenuation level c the controller gain is characterized in terms of the solution to a linear matrix inequality that can be easily solved by using standard software packages a simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures

robust h sub spl infin filtering for stochastic time delay systems with missing measurements in this paper the robust hinfin filtering problem is studied for stochastic uncertain discrete time delay systems with missing measurements the missing measurements are described by a binary switching sequence satisfying a conditional probability distribution we aim to design filters such that for all possible missing observations and all admissible parameter uncertainties the filtering error system is exponentially mean square stable and the prescribed hinfin performance constraint is met in terms of certain linear matrix inequalities lmis sufficient conditions for the solvability of the addressed problem are obtained when these lmis are feasible an explicit expression of a desired robust hinfin filter is also given an optimization problem is subsequently formulated by optimizing the hinfin filtering performances finally a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach

weak sharpness for gap functions in vector variational inequalities abstract in this paper characterizations of the set of solutions for vvi are presented by using scalarization approaches the set of solutions of vvi is shown to be the set of weak sharpness for gap functions of some scalarization of vvi and for gap functions of vvi under semi strong monotonicity some examples are given to illustrate these results

robust estimation for neural networks with randomly occurring distributed delays and markovian jump coupling this paper studies the issue of robust state estimation for coupled neural networks with parameter uncertainty and randomly occurring distributed delays where the polytopic model is employed to describe the parameter uncertainty a set of bernoulli processes with different stochastic properties are introduced to model the randomly occurrences of the distributed delays novel state estimators based on the local coupling structure are proposed to make full use of the coupling information the augmented estimation error system is obtained based on the kronecker product a new lyapunov function which depends both on the polytopic uncertainty and the coupling information is introduced to reduce the conservatism sufficient conditions which guarantee the stochastic stability and the l 2 l infty performance of the augmented estimation error system are established then the estimator gains are further obtained on the basis of these conditions finally a numerical example is used to prove the effectiveness of the results

robust control for fuzzy dynamical systems uniform ultimate boundedness and optimality we propose a new approach for the control design of fuzzy dynamical systems the system may contain uncertainty which includes unknown parameter and input disturbance the uncertainty lies within a prescribed fuzzy set the control structure is deterministic and hence not if then rule based the desired controlled system performance includes uniform boundedness and uniform ultimate boundedness in addition we propose a quadratic cost index which reflects the fuzzy system performance we then formulate a control parameter design problem as a constrained optimization problem it is proven that the global solution to this problem always exists and is unique the closed form solution and the closed form minimum cost are derived

one hundred years of the design of experiments on and off the pages of biometrika the earliest important papers on planned experiments in biometrika appeared within a year of each other in 1917 and 1918 roughly speaking one was concerned with design optimality and industrial experiments the other with agricultural trials and blocking we find this approximate division of the subject into two parts helpful in describing its development and growth as a result of the hostility between fisher and karl pearson much of the development of designs for agriculture in the 1920s and 1930s occurred off the pages of biometrika despite this we are able to trace a coherent history of the development of the subject from field trials and response surface methods to clinical trials and bayesian versions of design optimality

weak sharp minima for convex infinite optimization problems in normed linear spaces in the present paper we study the characterization issue of the weak sharp minima properties for convex infinite optimization problems in normed linear spaces we develop a new approach to establi

intrinsic autoregressions and related models on the two dimensional lattice summary stationary autoregressions on a two dimensional lattice are generalized to intrinsic models where only increments are assumed to be stationary prediction formulae and the asymptotic behaviour of the semivariogram are derived for parameter estimation we propose an approximate maximum likelihood estimator a generalization of whittle s estimator it is derived also for general intrinsic models

conic positive definiteness and sharp minima of fractional orders in vector optimization problems abstract motivated by the fact that the usual positive definiteness does not work in an infinite space we introduce the concept of s positive definiteness with respect to an ordering cone in a general banach space and show that the s positive definiteness plays the same role as the usual positive definiteness in the finite dimensional case as applications we study sharp and weak sharp minima of fractional orders in vector optimization

weak sharp solutions of variational inequalities in hilbert spaces under some new conditions we present several equivalent and sufficient conditions for weak sharp solutions of variational inequalities in hilbert spaces and give a finite convergence result for a class of algorithms for solving variational inequalities

the linear l 1 estimator and the huber m estimator relationships between a linear l1 estimation problem and the huber m estimator problem can be easily established by their dual formulations the least norm solution of a linear programming problem studied by mangasarian and meyer siam j control optim 17 1979 pp 745 752 provides a key link between the dual problems based on the dual formulations we establish a local linearity property of the huber m estimators with respect to the tuning parameter gamma and prove that the solution set of the huber m estimator problem is lipschitz continuous with respect to perturbations of the tuning parameter gamma as a consequence the set of the linear l1 estimators is the limit of the set of the huber m estimators as gamma to 0 thus the huber m estimator problem has many solutions for small tuning parameter gamma if the linear l1 estimation problem has multiple solutions a recursive version of madsen and nielsen s algorithm siam j optim 3 1993 pp 223 235 based on computation of the huber m estimator is proposed for finding a linear l1 estimator

weak sharp minima in multicriteria linear programming in this short note we study the existence of weak sharp minima in multicriteria linear programming it is shown that weak sharp minimality holds for certain residual functions and gap functions

on joint design of intentionally introduced delay and controller gain for stabilization of second order oscillatory systems this paper focuses on stabilization of second order oscillatory systems using both feedback control and intentionally introduced time delay the argument principle is employed as a key technique to divide the parameter space of time delay and controller gain into several regions every admissible value in these regions moves the poles of the closed loop system towards the left of the complex plane such that stability improvement is achieved the concept of potent asymptotic stability is first introduced referring to the property that all the poles of the closed loop system are stable and lie on the left of open loop system poles in the complex plane analytical characterizations on parameter pairs of time delay and controller gain that result in potent asymptotic stability are established all the poles and corresponding root locus with respect to gain are examined numerical examples and simulations are given to illustrate the usefulness and merits of the theoretical results

a delay dependent approach to robust h sub spl infin filtering for uncertain discrete time state delayed systems a delay dependent approach to robust h sub spl infin filtering is proposed for linear discrete time uncertain systems with multiple delays in the state the uncertain parameters are supposed to reside in a polytope and the attention is focused on the design of robust filters guaranteeing a prescribed h sub spl infin noise attenuation level the proposed filter design methodology incorporates some recently appeared results such as moon s new version of the upper bound for the inner product of two vectors and de oliveira s idea of parameter dependent stability which greatly reduce the overdesign introduced in the derivation process in addition to the full order filtering problem the challenging reduced order case is also addressed by using different linearization procedures both full and reduced order filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities which can be solved via efficient interior point algorithms numerical examples have been presented to illustrate the feasibility and advantages of the proposed methodologies

weak sharp minima for piecewise linear multiobjective optimization in normed spaces abstract in a general normed space we consider a piecewise linear multiobjective optimization problem we prove that a cone convex piecewise linear multiobjective optimization problem always has a global weak sharp minimum property by a counter example we show that the weak sharp minimum property does not necessarily hold if the cone convexity assumption is dropped moreover under the assumption that the ordering cone is polyhedral we prove that a not necessarily cone convex piecewise linear multiobjective optimization problem always has a bounded weak sharp minimum property

reliable h_ infty control for discrete time fuzzy systems with infinite distributed delay in this paper the problem of reliable h control is investigated for discrete time takagi sugeno t s fuzzy systems with infinite distributed delay and actuator faults a discrete time homogeneous markov chain is used to represent the stochastic behavior of actuator faults in terms of a stochastic fuzzy lyapunov functional a sufficient condition is proposed to ensure that the resultant closed loop system is exponentially stable in the mean square sense with an h performance index based on the derived condition the reliable h control problem is solved and an explicit expression of the desired controller is also given the case of no failure in the actuator is also considered a numerical example is given to demonstrate that our results are effective and less conservative

randomness and degrees of irregularity the fundamental question are sequential data random arises in myriad contexts often with severe data length constraints furthermore there is frequently a critical need to delineate nonrandom sequences in terms of closeness to randomness e g to evaluate the efficacy of therapy in medicine we address both these issues from a computable framework via a quantification of regularity apen approximate entropy defining maximal randomness for sequences of arbitrary length indicating the applicability to sequences as short as n 5 points an infinite sequence formulation of randomness is introduced that retains the operational and computable features of the finite case in the infinite sequence setting we indicate how the foundational definition of independence in probability theory and the definition of normality in number theory reduce to limit theorems without rates of convergence from which we utilize apen to address rates of convergence of a deficit from maximal randomness refining the aforementioned concepts in a computationally essential manner representative applications among many are indicated to assess i random number generation output ii well shuffled arrangements and iii the quality of bootstrap replicates

improved criteria for the stabilization of t s fuzzy systems with actuator failures via a sampled data fuzzy controller abstract this paper studies a problem of the sampled data stabilization for takagi sugeno fuzzy systems with actuator failures an improved lyapunov functional is constructed which is dependent on the fuzzy membership functions fmfs and includes the sampling states with two sampling instants a new integral term including the fmfs is introduced into this lyapunov functional for the first time each term in this lyapunov functional need not be positive but it should be positive at sampling instants the variation range of the fmfs is taken into account in dealing with the derivative of this lyapunov functional as well then improved stabilization criteria guaranteeing a larger sampling interval are obtained by applying the developed fuzzy controller simulation examples are given to illustrate the effectiveness and less conservatism of the proposed method

gâteaux differentiability of the dual gap function of a variational inequality abstract in terms of the mapping involved in a variational inequality we characterize the g teaux differentiability of the dual gap function g and present several sufficient conditions for its directional derivative expression including one weaker than that of danskin j m danskin the theory of max min with applications siam journal on applied mathematics 14 1966 641 664 when the solution set of a variational inequality problem is contained in that of its dual problem the g teaux differentiability of g on the latter turns out to be equivalent to the conditions appearing in the authors recent results about the weakly sharp solutions of the variational inequality problem

merit functions in vector optimization we study the weak domination property and weakly efficient solutions in vector optimization problems in particular scalarization of these problems is obtained by virtue of some suitable merit functions some natural conditions to ensure the existence of error bounds for merit functions are also given