Robust filtering with stochastic nonlinearities and multiple missing measurements

This is the post print version of the article. The official published version can be obtained from the link - Copyright 2009 Elsevier LtdThis paper is concerned with the filtering problem for a class of discrete-time uncertain stochastic nonlinear time-delay systems with both the probabilistic missing measurements and external stochastic disturbances. The measurement missing phenomenon is assumed to occur in a random way, and the missing probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution over the interval . Such a probabilistic distribution could be any commonly used discrete distribution over the interval . The multiplicative stochastic disturbances are in the form of a scalar Gaussian white noise with unit variance. The purpose of the addressed filtering problem is to design a filter such that, for the admissible random measurement missing, stochastic disturbances, norm-bounded uncertainties as well as stochastic nonlinearities, the error dynamics of the filtering process is exponentially mean-square stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the exponential mean-square stability of the filtering error, and then the filter parameters are characterized by the solution to a set of LMIs. Illustrative examples are exploited to show the effectiveness of the proposed design procedures.This work was supported in part by the Shanghai Natural Science Foundation under Grant 07ZR14002, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, an International Joint Project sponsored by the Royal Society of the UK, the Nuffield Foundation of the UK under Grant NAL/00630/G and the Alexander von Humboldt Foundation of Germany

Niveau d’Instruction de la Mère et État Nutritionnel des Enfants de Moins de Cinq ans au Bénin

Cette étude vise à examiner les effets du niveau d’instruction de la mère sur l’état nutritionnel des enfants de moins de cinq au Bénin. Utilisant les données issues de l’enquête démographique et de santé (EDSB-V) de 2018, ce travail adopte une stratégie d’estimation qui contrôle le biais de sélection et l’endogénéité potentielle du niveau d’instruction de la mère pour examiner la relation entre l’instruction de la mère et l’état nutritionnel des enfants. Les résultats indiquent que l’instruction de la mère est un facteur déterminant de l’état nutritionnel des enfants au Bénin. L’effet est plus important et robuste sur le retard de croissance, l’insuffisance pondérale et l’émaciation. Aussi, le niveau d’instruction des mères nécessaire pour faire des réductions significatives de la malnutrition infantile est au moins le niveau secondaire. Les résultats obtenus montrent que les politiques de scolarisation des femmes doivent être incorporées dans les stratégies nationales de nutrition.   This study aims to examine the effects of mother’s education level on the children’s nutritional status in Benin. Using data from the 2018 Demographic and Health Survey (EDSB-V), this work adopts an estimation strategy that controls for selection bias and potential endogeneity of the mother's education level to examine the relationship between mother's education and children's nutritional status. The findings indicate that the mother’s education is a determining factor of the children’s nutritional status in Benin. The effect is larger and more robust on stunting, underweight and wasting. Also, the mothers’ education level needed to make significant reductions in child malnutrition is at least high school. The obtained results show that women education policies must be incorporated into national nutrition strategies

Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements

Copyright @ 2012 ElsevierIn this paper, the extended Kalman filtering problem is investigated for a class of nonlinear systems with multiple missing measurements over a finite horizon. Both deterministic and stochastic nonlinearities are included in the system model, where the stochastic nonlinearities are described by statistical means that could reflect the multiplicative stochastic disturbances. The phenomenon of measurement missing occurs in a random way and the missing probability for each sensor is governed by an individual random variable satisfying a certain probability distribution over the interval [0,1]. Such a probability distribution is allowed to be any commonly used distribution over the interval [0,1] with known conditional probability. The aim of the addressed filtering problem is to design a filter such that, in the presence of both the stochastic nonlinearities and multiple missing measurements, there exists an upper bound for the filtering error covariance. Subsequently, such an upper bound is minimized by properly designing the filter gain at each sampling instant. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati-like difference equations that are of a form suitable for recursive computation in online applications. An illustrative example is given to demonstrate the effectiveness of the proposed filter design scheme.This work was supported in part by the National 973 Project under Grant 2009CB320600, National Natural Science Foundation of China under Grants 61028008, 61134009 and 60825303, the State Key Laboratory of Integrated Automation for the Process Industry (Northeastern University) of China, the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Effets du Niveau d’Instruction de la Mère sur l’État Nutritionnel des Enfants de Moins de Cinq ans au Bénin

Se basant sur la théorie de l’allocation du temps de Becker (1965), cet article vise à examiner les effets du niveau d’instruction de la mère sur l’état nutritionnel des enfants de moins de cinq ans au Bénin. Utilisant les données issues de l’enquête démographique et de santé (EDSB-V) de 2018 portant sur un échantillon de 11631 enfants de moins de cinq ans, il adopte une stratégie d’estimation qui contrôle le biais de sélection et l’endogénéité potentielle du niveau d’instruction de la mère pour examiner l’effet du niveau d’instruction de la mère sur l’état nutritionnel de l’enfant. Les résultats indiquent que l’instruction de la mère est un facteur déterminant de l’état nutritionnel des enfants au Bénin. L’effet est plus important et robuste sur le retard de croissance, l’insuffisance pondérale et l’émaciation. Aussi, le niveau d’instruction des mères nécessaire pour faire la réduction significative de la malnutrition infantile est-il au moins le niveau secondaire. Les résultats obtenus montrent que les politiques de scolarisation des femmes doivent être incorporées dans les stratégies nationales de nutrition.   Based on a theory of the allocation of time Becker (1965), this study aims to examine the effects of the mother’s education level on the children’s nutritional status under five in Benin. Using data from the 2018 Demographic and Health Survey (EDSB-V) on a sample of 11.631 children under the age of five, this work adopts an estimation strategy that controls for selection bias and potential endogeneity of the mother's education level to examine the effect of the mother's education and children's nutritional status. The findings indicate that the mother’s education is a determining factor in the children’s nutritional status in Benin. The effect is larger and more robust on stunting, underweight, and wasting. In addition, the mother’s education level needed to make significant reductions in child malnutrition is at least high school. The obtained results show that women’s education policies must be incorporated into national nutrition strategies

Niveau d’Instruction de la Mère et État Nutritionnel des Enfants de Moins de Cinq ans au Bénin

Cette étude vise à examiner les effets du niveau d’instruction de la mère sur l’état nutritionnel des enfants de moins de cinq au Bénin. Utilisant les données issues de l’enquête démographique et de santé (EDSB-V) de 2018, ce travail adopte une stratégie d’estimation qui contrôle le biais de sélection et l’endogénéité potentielle du niveau d’instruction de la mère pour examiner la relation entre l’instruction de la mère et l’état nutritionnel des enfants. Les résultats indiquent que l’instruction de la mère est un facteur déterminant de l’état nutritionnel des enfants au Bénin. L’effet est plus important et robuste sur le retard de croissance, l’insuffisance pondérale et l’émaciation. Aussi, le niveau d’instruction des mères nécessaire pour faire des réductions significatives de la malnutrition infantile est au moins le niveau secondaire. Les résultats obtenus montrent que les politiques de scolarisation des femmes doivent être incorporées dans les stratégies nationales de nutrition.   This study aims to examine the effects of mother’s education level on the children’s nutritional status in Benin. Using data from the 2018 Demographic and Health Survey (EDSB-V), this work adopts an estimation strategy that controls for selection bias and potential endogeneity of the mother's education level to examine the relationship between mother's education and children's nutritional status. The findings indicate that the mother’s education is a determining factor of the children’s nutritional status in Benin. The effect is larger and more robust on stunting, underweight and wasting. Also, the mothers’ education level needed to make significant reductions in child malnutrition is at least high school. The obtained results show that women education policies must be incorporated into national nutrition strategies

H-infinity filtering with randomly occurring sensor saturations and missing measurements

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ElsevierIn this paper, the H∞ filtering problem is investigated for a class of nonlinear systems with randomly occurring incomplete information. The considered incomplete information includes both the sensor saturations and the missing measurements. A new phenomenon of sensor saturation, namely, randomly occurring sensor saturation (ROSS), is put forward in order to better reflect the reality in a networked environment such as sensor networks. A novel sensor model is then established to account for both the ROSS and missing measurement in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. Based on this sensor model, a regional H∞ filter with a certain ellipsoid constraint is designed such that the filtering error dynamics is locally mean-square asymptotically stable and the H∞-norm requirement is satisfied. Note that the regional l2 gain filtering feature is specifically developed for the random saturation nonlinearity. The characterization of the desired filter gains is derived in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite program method. Finally, a simulation example is employed to show the effectiveness of the filtering scheme proposed in this paper.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61028008 and 60974030, the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany

Robust H∞ control for a class of nonlinear discrete time-delay stochastic systems with missing measurements

This is the post print version of the article. The official published version can be obtained from the link - Copyright 2009 Elsevier LtdThis paper is concerned with the problem of robust H∞ output feedback control for a class of uncertain discrete-time delayed nonlinear stochastic systems with missing measurements. The parameter uncertainties enter into all the system matrices, the time-varying delay is unknown with given low and upper bounds, the nonlinearities satisfy the sector conditions, and the missing measurements are described by a binary switching sequence that obeys a conditional probability distribution. The problem addressed is the design of an output feedback controller such that, for all admissible uncertainties, the resulting closed-loop system is exponentially stable in the mean square for the zero disturbance input and also achieves a prescribed H∞ performance level. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are first derived to guarantee the existence of the desired controllers, and then the controller parameters are characterized in terms of linear matrix inequalities (LMIs). A numerical example is exploited to show the usefulness of the results obtained.This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor Dragan Nešic under the direction of Editor Hassan K. Khalil. This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the City University of Hong Kong under Grant 7001992, the Royal Society of the U.K. under an International Joint Project, the Natural Science Foundation of Jiangsu Province of China under Grant BK2007075, the National Natural Science Foundation of China under Grant 60774073, and the Alexander von Humboldt Foundation of Germany

Habitat range shift and prediction of the potential future distribution of Ricinodendron heudelotii (Baill.) Heckel in Benin (West Africa)

Open Access ArticleRicinodendron heudelotii (Baill.) Heckel is an important nutraceutical reservoir. Its Sustainable exploitation requires information on its potential distribution in the current context of rapid population growth and climate change threats. This study aimed to map the suitable areas for its domestication and conservation under current and future climate conditions in Benin. Occurrence data were recorded and combined with the environmental layers of two climatic scenarios (optimistic RCP 4.5 and pessimistic RCP 8.5) following the biodiversity modelling approach (biomod2). Currently, about four percent (5082 Km2) of the country’s area mainly located in the sub-humid and the humid zones were potentially suitable for R. heudelotii distribution. Under future climatic conditions the potentially suitable areas were mainly in the sub-humid zone, but almost all the highly suitable areas located in the humid zone will become medium suitable areas by the years 2055 and 2085 horizons. This study shows that, whatever the future climatic scenarios, R. heudelotii will substantially maintain the size of its range across the country. These findings allow undertaking anticipated actions to better adapt to the potential effects of climate change and to better guide policies for the conservation and development of forest resources

A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements

In this paper, the recursive state estimation problem is investigated for an array of discrete timevarying coupled stochastic complex networks with missing measurements. A set of random variables satisfying certain probabilistic distributions is introduced to characterize the phenomenon of the missing measurements, where each sensor can have individual missing probability. The Taylor series expansion is employed to deal with the nonlinearities and the high-order terms of the linearization errors are estimated. The purpose of the addressed state estimation problem is to design a time-varying state estimator such that, in the presence of the missing measurements and the random disturbances, an upper bound of the estimation error covariance can be guaranteed and the explicit expression of the estimator parameters is given. By using the Riccati-like difference equations approach, the estimator parameter is characterized by the solutions to two Riccati-like difference equations. It is shown that the obtained upper bound is minimized by the designed estimator parameters and the proposed state estimation algorithm is of a recursive form suitable for online computation. Finally, an illustrative example is provided to demonstrate the feasibility and effectiveness of the developed state estimation scheme.National Natural Science Foundation of China under Grants 61329301, 61273156 61333012, 11301118 and 11271103, the Youth Science Foundation of Heilongjiang Province of China under Grant QC2015085, the China Postdoctoral Science Foundation under Grants 2015T80482 and 2014M560376, Jiangsu Planned Projects for Postdoctoral Research Funds under Grant 1402004A, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany