convergence analysis of an online approach to parameter estimation problems based on binary observations in this paper we present an online identification method to the problem of parameter estimation from binary observations a recursive identification algorithm with low storage requirements and computational complexity is derived we prove the convergence of this method provided that the input signal satisfies a strong mixing property some simulation results are then given in order to illustrate the properties of this method under various scenarios this method is appealing in the context of micro electronic devices since it only requires a 1 bit analog to digital converter with low power consumption and minimal silicon area

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

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

censored regression local linear approximations and their applications abstract various statistical tools are available for modeling the relationship between response and covariate if the data are fully observable in the situation of censored data however those tools are no longer directly applicable this article provides an easily implemented methodology for modeling the association based on censored data the form of the regression relationship will be completely determined by the data no assumptions are made about this form basic ideas behind the methodology are to transform the observed data in an appropriate simple way and then to apply a locally weighted least squares regression the proposed estimator involves a variable bandwidth that automatically adapts to the design of the data points that the methodology is very easy to implement is illustrated by several examples including simulation studies and an analysis of the stanford heart transplant data and the primary biliary cirrhosis data several theoretical considerations are reflected in the examples fina

nonparametric and nonlinear reconstruction of surfaces from qualitative observations abstract the aim of this paper is to discuss the problem of reconstructing surfaces from qualitative observations the problem statement is motivated by examples from testing quality of materials the proposed estimator is nonlinear and nonparametric its consistency is discussed and the rate of convergence is given then we propose its smoothed and adaptive version and validate it using simulated data

on the design of observer based controller of linear neutral delay differential systems in this note the observer based control problem for a class of linear delay differential systems of neutral type is investigated using the lyapunov method a criterion for asymptotic stability is derived in terms of matrix inequalities which solved by convex optimization algorithms a numerical example is given to illustrate the proposed method

delay range dependent observer based control of nonlinear systems under input and output time delays observer based control of nonlinear systems under input output delays is studied time varying nature of delays is incorporated for the controller design delay range dependent observer based control is reported decoupling technique is applied to compute controller and observer gains the control scheme is tested to control a one link flexible joint robotic arm the problem of designing observer based controller for a class of nonlinear time delay systems subjected to input and output time varying delays is addressed in this paper more incisively a delay range dependent criterion incorporating variation of delays between known lower and upper bounds is established for control of nonlinear time delay systems the proposed methodology ensures asymptotic stability of the closed loop system s state and the estimation error between states of the system and observer by application of a lyapunov krasovskii functional jensen s inequality standard matrix inequality procedures luenberger type observer delay interval bounds and delay derivative limits observer based controller synthesis approach using nonlinear matrix inequalities for the nonlinear time delay systems is provided further a decoupling approach is employed to render a simpler condition for the observer and the controller synthesis a novel observer based control scheme for the linear time delay systems with interval time varying input as well as output lags is derived from the proposed control strategy the traditional delay dependent controller design incorporating zero lower bound of the delay for the time delay systems is a particular scenario of the projected delay range dependent approach the proposed decoupled observer based controller synthesis condition is cast into linear matrix inequalities by means of the cone complementary linearization approach finally a numerical simulation example of control of one link flexible joint robotic arm is provided to verify the proposed design methodology

local convergence analysis of conjugate gradient methods for solving algebraic riccati equations necessary and sufficient conditions are given for local convergence of the conjugate gradient cg method for solving symmetric and nonsymmetric algebraic riccati equations for these problems the frobenius norm of the residual matrix is minimized via the cg method and convergence in a neighborhood of the solution is predicated on the positive definiteness of the associated hessian matrix for the nonsymmetric case the hessian eigenvalues are determined by the squares of the singular values of the closed loop sylvester operator in the symmetric case the hessian eigenvalues are closely related to the squares of the closed loop lyapunov singular values in particular the hessian is positive definite if and only if the associated operator is nonsingular the invertibility of these operators can be expressed as a noncancellation condition on the eigenvalues of the closed loop matrices

periodic output feedback stabilization of neutral systems a new feedback control technique called periodic output feedback is investigated in the context of infinite dimensional linear systems modeled by neutral functional differential equations in this method discrete output samples are multiplied by a periodic gain function to generate a continuous feedback control this work focuses on stabilization of neutral systems with delayed control modeled in the state space w sub 2 sup 1 r 0 r sup n spl times l sup 2 r 0 r sup p where w sub 2 sup 1 r 0 r sup n denotes the sobolev space of r sup n valued absolutely continuous functions with square integrable derivatives on r 0 we show that a class of these systems can be stabilized by periodic output feedback even though their input operators are unbounded we overcome this difficulty by representing the system state using an abstract integral variation of constants formula an algorithm is presented at the end of this paper to construct a periodic output feedback gain function an example is provided to illustrate the construction of the gain function

almost everywhere convergence of a recursive regression function estimate and classification corresp it is shown that the recursive kernel estimate of the regression function e y x x is consistent at almost every x mu regardless of the distribution mu of x thus the result is distribution free from this we show that the risk for a suitable classification rule derived from the estimate converges to bayes risk no matter what the class distributions are

linear systems identification from random threshold binary data a new identification problem of estimating parameters of linear dynamic systems from random threshold binary observations of its output and input is stated the only available data are collected as a result of checking whether a signal reached a randomly specified threshold at a randomly chosen instant of time the proposed estimation algorithm is based on the celebrated von neumann theorem which was earlier used mainly for generating random numbers strong consistency of parameters estimate from low cost output binary observations is proved assuming deterministic input signal of a finite duration possibilities of relaxing the assumption used in the theoretical part of the paper are considered by means of simulations

on the solution of a class of algebraic matrix riccati equation we consider the algebraic matrix riccati equation of control theory arising with a scalar control it is shown that if the riccati equation is taken in phase variable canonical form the solution may be effected by solving a scalar polynomial equation whose degree is that of the unknown matrix the resolution of the problem involves only elementary algebraic operations on the solution of the scalar polynomial equation an illustrative numerical example is given

strassen s invariance principle for random subsequences necessary and sufficient conditions are given for strassen s invariance principle 6 in case a random subsequence is considered a few iterated logarithm laws for random subsequences are derived as corollaries these results generalize in particular those obtained by chow et al 1

identification of fir systems based on quantized output measurements a quadratic programming based method this technical note proposes a quadratic programming qp based method for identification of finite impulse response fir dynamic systems from quantized or binary data the main idea of the proposed method is to reformulate this identification problem usually viewed as a nonlinear estimation problem with discontinuous nonlinearities in the form of a standard qp problem which is a convex optimization problem and can be solved efficiently the so called complete input conditions to ensure the unique solution of the qp problem are developed and the consistency of the estimated parameters is established under the complete input conditions numerical examples demonstrate the effectiveness of the proposed method

an alternate calculation of the discrete time kalman filter gain and riccati equation solution we describe an algorithm to calculate the steady state kalman filter gain and riccati equation solution for a discrete time kalman filter our algorithm makes use of an approximate autoregressive model for the one step predictor and only requires the solutions to linear equations all of the nonlinear calculations can be made explicitly

on robust h filter design for uncertain neural systems lmi optimization approach this article deals with the robust h filtering problem for neutral delay differential systems with parametric uncertainties a linear matrix inequality lmi approach is proposed to design the robust h filter such that the filtering system remains asymptotically stable and the bound of h norm is minimized the lyapunov stability theory is used for analysis of the system a numerical example is provided to illustrate the validity of proposed design approach

the application of random reference sequences to the reconstruction of clipped differentiable signals the estimation of analog waveforms s t from their clipped contaminated samples is considered for differentiable signals s t appropriate estimates are established and their performance is investigated error bounds and convergence rates are derived which improve with the degree of differentiability of the signal s t the analytical results are supplemented by a simulation study

identification of wiener systems with clipped observations in this paper we consider the parametric version of wiener systems where both the linear and nonlinear parts are identified with clipped observations in the presence of internal and external noises also the static functions are allowed noninvertible we propose a classification based support vector machine svm and formulate the identification problem as a convex optimization the solution to the optimization problem converges to the true parameters of the linear system if it is an finite impulse response fir system even though clipping reduces a great deal of information about the system characteristics in identifying a wiener system with a stable infinite impulse response iir system an fir system is used to approximate it and the problem is converted to identifying the fir system together with solving a set of nonlinear equations this leads to biased estimates of parameters in the iir system while the bias can be controlled by choosing the order of the approximated fir system

on guaranteed cost control of neutral systems by retarded integral state feedback in this paper the guaranteed cost control problem for a class of neutral delay differential systems with a given quadratic cost functions is investigated the problem is to design a memory state feedback controller such that the closed loop system is asymptotically stable and the closed loop cost function value is not more than a specified upper bound some criteria for the existence of such controllers is derived based on the linear matrix inequality lmi approach combined with the lyapunov method a parameterized characterization of the controllers is given in terms of the feasible solutions to the certain lmis a numerical example is given to illustrate the proposed method

error bounds for reconstruction of a function f from a finite sequence operatorname sgn f t_i x_i consider reconstructing a function f t 0 leqq t leqq 1 from knowledge only of t i s i 1 leqq i leqq n where s i operatorname sgn f t i x i 1 leqq i leqq n and the x i are additive corruptions without the components x i f could not be reconstructed however for f continuous and for random uniform noise x masry and cambanis ieee trans inform theory it 26 1980 pp 50 58 it 27 1981 pp 84 96 show that f can be consistently estimated almost surely and in mean square as n to infty and establish rates of pointwise convergence through a somewhat different treatment in which the approximation of f t i is identified as a numerical integration problem rather than a statistical problem we obtain simple exact bounds on the error of estimation allow the noise x to be arbitrary random or deterministic and deal with the case of f having discontinuities the bounds yield substantially improved rates of convergence when the noise values x i

the reconstruction of analog signals from the sign of their noisy samples the reconstruction of a continuous time signal s t from the sign of its deliberately contaminated samples is considered sequential generally nonlinear estimates of s t are established and their performance is studied error bounds and convergence rates are derived the signal s t need not be band limited the convergence rates obtained here are faster than those obtained previously for nonsequential estimates the degradation in the reconstruction of the signal due to transmission over a noisy channel is also investigated and bounds on the additional error are obtained

some simple criteria for stability of neutral delay differential systems this paper deals with the stability of linear neutral delay differential systems some simple criteria for delay independent stability of this class of problems which are described by evaluating the measure and norm of corresponding matrices are presented the main results proposed in this study are sharper than those reported in the literature

new delay dependent non fragile h observer based control for continuous time delay systems the problem of the delay dependent non fragile h observer based control for a class of continuous time delay systems is investigated in this paper the additive gain variations under consideration are contained in both the controller gain and obhsiunserver gain delay dependent criteria are derived to guarantee the stability of the non fragile h observer based control system using the lyapunov functional approach the controller and observer gains are given from the lmi feasible solutions based on the result of this paper the constraint of matrix equality is not necessary for designing the non fragile h observer based controls computer software matlab can be applied to solve all the proposed results finally a numerical example is illustrated to show the improvement of this paper

some numerical considerations and newton s method revisited for solving algebraic riccati equations analyzes some of the numerical aspects of solving the algebraic riccati equation are this analysis applies to both the symmetric and unsymmetric cases the author reconsiders the numerically relevant problems of balancing the are and the conditioning properties of the are and shows how these can be exploited by a solution algorithm he proposes an estimator for the condition number of the sylvester equation ax xb c based on iterative refinement also he interprets newton s method as a sequence of similarity transformations on the underlying system matrix this closes the gap between so called global and iterative methods for solving the are and also suggests an altogether revised implementation of newton s method one of the advantages of this revised implementation is that in the case where newton s method converges to a solution different from the desired solution enough information emerges to allow a switch to the desired solution the author examines the roundoff properties of the new algorithm and provides implementation considerations and numerical examples to highlight pros and cons

hammerstein system identification by non parametric regression estimation a discrete time multiple input non linear hammerstein system is identified the dynamical subsystem is recovered using the standard correlation method the main results concern estimation of the non linear memoryless subsystem no conditions concerning the functional form of the transform characteristic of the subsystem are made and an algorithm for estimation of the characteristic is given the algorithm is simply a non parametric kernel estimate of the regression function calculated from the dependent data it is shown that the algorithm converges to the characteristic of the subsystem in the pointwise as well as the global sense for sufficiently smooth characteristics the rate of convergence is o n 1 2 d in probability where d is the dimension of the input variable

a weighted least squares approach to parameter estimation problems based on binary measurements we present a new approach to parameter estimation problems based on binary measurements motivated by the need to add integrated low cost self test features to microfabricated devices this approach is based on the use of original weighted least squares criteria as opposed to other existing methods it requires no dithering signal and it does not rely on an approximation of the quantizer in this technical note we focus on a simple choice for the weights and establish some asymptotical properties of the corresponding criterion to achieve this the assumption that the quantizer s input is gaussian and centered is made in this context we prove that the proposed criterion is locally convex and that it is possible to use a simple gradient descent to find a consistent estimate of the unknown system parameters regardless of the presence of measurement noise at the quantizer s input

feedback stabilization of neutral systems via the transformation technique within the class of delay systems a neutral system may be distinguished by the possible presence of a neutral root chain an infinite chain of eigenvalues in a vertical strip of the complex plane assuming that such a neutral root chain if it exists is stable this work shows how our method of transformation can be extended to obtain feedback controllers for this class of neutral systems

stabilization analysis for discrete time systems with time delay the stabilization problem for a class of discrete time systems with time varying delay is investigated by constructing an augmented lyapunov function some sufficient conditions guaranteeing exponential stabilization are established in forms of linear matrix inequality lmi technique when norm bounded parameter uncertainties appear in the delayed discrete time system a delay dependent robust exponential stabilization criterion is also presented all of the criteria obtained in this paper are strict linear matrix inequality conditions which make the controller gain matrix can be solved directly three numerical examples are provided to demonstrate the effectiveness and improvement of the derived results

nonparametric identification of a particular nonlinear time series system a nonlinear time series system is identified the system has a cascade structure that is it consists of a nonlinear memoryless element followed by a dynamic linear system given a gaussian input a hermite series based method for recovering the system nonlinearity is presented the proposed identification procedure is nonparametric since it is able to be consistent for a broad class of nonpolynomial characteristics the consistency and rate of convergence of the procedure are established also some data driven methods for selecting the optimal number of terms in the procedure are proposed the results are illustrated by a numerical example

defect correction method for the solution of algebraic riccati equations the solution of discrete and continuous algebraic riccati equations is considered it is shown that if an approximate solution is obtained then the defect for this solution again solves an algebraic riccati equation of the same form and that the system properties of detectability and stabilizability are inherited by this defect equation on the basis of these results a general defect correction method is proposed and numerical examples are given for the use of this method in combination with a bunse gerstner and v mehrmann s 1986 sr method