Estimation of the state levels of a discrete-time, finite-state Markov chain hidden in coloured Gaussian noise and subjected to unknown nonlinear distortion is considered. If the nonlinear distortion has almost linear behaviour for small values near zero or for large values, extreme value theory can be applied to the level estimation problem, resulting in simple estimation algorithms. The extre...

In this paper, we propose a class of partially nonlinear models, and develop two new estimation procedures for these models. Asymptotic normality of the resulting estimates are established. We further propose an estimation procedure and a generalized likelihood ratio test for the baseline function in partially nonlinear models. Asymptotic properties of the newly proposed estimation procedure an...

Pose estimation from an arbitrary number of 2-D to 3D feature correspondences is often done by minimising a nonlinear criterion function using one of the minimal representations for the orientation. However, there are many advantages in using unit quaternions to represent the orientation. Unfortunately, a straightforward formulation of the pose estimation problem based on quaternions results in...

Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/pharmacodynamic phenotypes. An EM algorithm for maximum likelihood estimation approach is developed and uses sampling-based methods to implement the expectation step, that results in an analytically tractable maximization step. A benefit of the approach is that no model linearizat...

This paper considers the problem of universal transform coding based on estimating the Karhunen-Lo eve transform from quantized data. The use of quantized data in the estimation allows the encoder and decoder to maintain the same state without any side information. A theorem is presented that proves, under certain conditions, that consistent estimation of all the required moments is possible fr...

This paper deals with the state estimation of nonlinear systems. Our approach is based on the representation of a nonlinear system with the help of a decoupled multiple model. This kind of multiple model constitutes an alternative to the classic Takagi-Sugeno multiple model. Indeed, in opposition to this last, in the decoupled multiple model the dimension (i.e. the number of states) of the subm...

This paper deals with the problem of nonlinear states estimation in batch chemical processes. It presents a reduced-order nonlinear observer approach to perform the estimation. The proposed method allows adjustment of the speed of convergence towards zero of the estimation error. The stability properties of the model-based observer are analytically treated in order to show the conditions under ...

A new class of adaptive nonlinear H∞ control for robotic manipulators is proposed in this manuscript. Those control strategies are derived as solutions of particular nonlinear H∞ control problems, where both disturbances and estimation errors of unknown system parameters are regarded as exogenous disturbances to the processes, and the 2 gains from those uncertainties to generalized outputs are ...

The paper deals with the problems of control and state estimation for nonlinear dynamical control system described by differential equations with unknown but bounded initial states. The nonlinear function in the right-hand part of a differential system is assumed to be of quadratic type with respect to state variable. Basing on the well-known results of ellipsoidal calculus developed for linear...

Correspondence: wang4896@126. com Department of Mathematics, Hechi University, Yizhou, Guangxi 546300, P. R. China Abstract In this article, we discuss some generalized retarded nonlinear integral inequalities, which not only include nonlinear compound function of unknown function but also include retard items, and give upper bound estimation of the unknown function by integral inequality techn...