Shanghai Academy of Systems Science

Shanghai, China

Shanghai Academy of Systems Science

Shanghai, China
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Gao J.,Shanghai JiaoTong University | Chen Z.,Shanghai JiaoTong University | Cai Y.,Shanghai JiaoTong University | Xu X.,Shanghai JiaoTong University | And 2 more authors.
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

We investigate a weighted self-propelled agent system, wherein each agent's direction is determined by its spatial neighbors' directions with exponential weights according to the neighbor numbers. In order to describe the fact that some agents with more neighbors might have larger influence on its neighbors, we introduce a scaling exponent of the neighbor number between 0 and ∞. When the exponent is equal to 1, the convergence efficiency is enhanced in our simulation. Furthermore, as the exponent increases, i.e., the effect of weight becomes stronger, the network of agents becomes easier to achieve direction consensus. © 2010 The American Physical Society.


Chen Z.,Shanghai JiaoTong University | Gao J.,Shanghai JiaoTong University | Cai Y.,Shanghai JiaoTong University | Xu X.,University of Shanghai for Science and Technology | Xu X.,Shanghai Academy of Systems Science
Physica A: Statistical Mechanics and its Applications | Year: 2011

We study the effects of mobility on the evolution of cooperation among mobile players, which imitate collective motion of biological flocks and interact with neighbors within a prescribed radius R. Adopting the the prisoner's dilemma game and the snowdrift game as metaphors, we find that cooperation can be maintained and even enhanced for low velocities and small payoff parameters, when compared with the case that all agents do not move. But such enhancement of cooperation is largely determined by the value of R, and for modest values of R, there is an optimal value of velocity to induce the maximum cooperation level. Besides, we find that intermediate values of R or initial population densities are most favorable for cooperation, when the velocity is fixed. Depending on the payoff parameters, the system can reach an absorbing state of cooperation when the snowdrift game is played. Our findings may help understanding the relations between individual mobility and cooperative behavior in social systems. © 2011 Elsevier B.V. All rights reserved.


Chen Z.,Shanghai JiaoTong University | Gao J.,Shanghai JiaoTong University | Cai Y.,Shanghai JiaoTong University | Xu X.,University of Shanghai for Science and Technology | Xu X.,Shanghai Academy of Systems Science
Physica A: Statistical Mechanics and its Applications | Year: 2011

We investigate an evolutionary prisoner's dilemma game among self-driven agents, where collective motion of biological flocks is imitated through averaging directions of neighbors. Depending on the temptation to defect and the velocity at which agents move, we find that cooperation can not only be maintained in such a system but there exists an optimal size of interaction neighborhood, which can induce the maximum cooperation level. When compared with the case that all agents do not move, cooperation can even be enhanced by the mobility of individuals, provided that the velocity and the size of neighborhood are not too large. Besides, we find that the system exhibits aggregation behavior, and cooperators may coexist with defectors at equilibrium. © 2010 Elsevier B.V. All rights reserved.


Cai Y.-Z.,Shanghai JiaoTong University | Pan N.,Shanghai JiaoTong University | Xu X.-M.,Shanghai JiaoTong University | Xu X.-M.,Shanghai Academy of Systems Science | Xu X.-M.,University of Shanghai for Science and Technology
Kongzhi yu Juece/Control and Decision | Year: 2010

The H∞ filtering for networked control systems with stochastic transmission delay longer than a sampling period and data packet dropout is studied. For the given packet dropout, the filtering error system is modeled as an asynchronous dynamical system with rate constraints on two events. The sufficient condition for guaranteeing the exponential stability and the H∞ constraint of the filtering error system is given by using the theory of asynchronous dynamical systems. The corresponding filter is designed by solving a set of matrix inequalities. The simulation result shows the validity and effectiveness of this method.


Lu J.,Shanghai JiaoTong University | Cai Y.,Shanghai JiaoTong University | Xu L.,Akita Prefectural University | Xu X.,Shanghai JiaoTong University | And 2 more authors.
Proceedings of the 30th Chinese Control Conference, CCC 2011 | Year: 2011

This paper addresses the optimal filtering problem for a kind of local strongly coupled systems. We introduce a local strongly coupled system with communication between the nodes. Applying the standard kalman filter design procedures to such systems is difficult because of transmission delay and intermittent communication. By using the stochastic theory and state augmentation technique, we present the optimal filtering problem in terms of the full system dynamics. The numerical simulations not only show the effectiveness of the proposed filtering method, but also illustrate the complex random phenomenon in local strongly coupled systems. © 2011 Chinese Assoc of Automati.


Zhang Q.,Shanghai JiaoTong University | Wang R.,Chinese Flight Test Establishment | Cai Y.,Shanghai JiaoTong University | Xu X.,Shanghai JiaoTong University | And 2 more authors.
Journal of Computational Information Systems | Year: 2012

Nonnegative matrix factorization (NMF) is an unsupervised learning method for low-rank approximation of nonnegative data. Discriminative information and geometric structure in the data are missing in the standard NMF method. In this paper, we present a variation of NMF which is equipped with both these ingredients, such that the data manifold is respected and label information is incorporated. Based on the Improved Local Tangent Space Alignment (ILTSA), we regularize NMF by within-class and between-class local tangent space alignments, leading to manifold regularized discriminant NMF (MRDNMF), where we minimize the approximation error while contracting intra-class neighborhoods and expanding inter-class neighborhoods in the decomposition. We develop a novel multiplicative update method for MRDNMF and present monotonic convergence analysis. Experimental results on ORL and PIE face databases demonstrate the effectiveness of the proposed method for face recognition application. © 2011 by Binary Information Press.


Zhang Q.,Shanghai JiaoTong University | Wang R.,Chinese Flight Test Establishment | Cai Y.,Shanghai JiaoTong University | Xu X.,Shanghai JiaoTong University | And 2 more authors.
Journal of Computational Information Systems | Year: 2012

Improved Local Tangent Space Alignment (ILTSA) is a recent nonlinear dimensionality reduction method but there exists the out-of-sample problem. In this paper, based on linearization and discriminant extension of ILTSA, a novel feature extraction method named null space local tangent space alignment discriminant mapping (NSLTSADM) is proposed. Based on combination of nonparametric discriminant analysis between-class metric and local within-class tangent space alignment, NSLTSADM can preserve both local geometry structure and classification information. In face recognition application, we propose an augmented Gabor-like complex wavelet transform which can efficiently alleviate the illumination and expression variation effect. An approach for face recognition based on the fusion of local and holistic features is developed. Experimental results on Yale and PIE face databases demonstrate the effectiveness of the proposed face recognition method. 1553-9105/Copyright © 2012 Binary Information Press.


Zhang Q.,Shanghai JiaoTong University | Niu H.,Shanghai Aerospace Control Engineering Institute | Cai Y.,Shanghai JiaoTong University | Xu X.,Shanghai JiaoTong University | And 2 more authors.
ICIC Express Letters, Part B: Applications | Year: 2012

In this paper, a novel face recognition method based on combination of augmented Gabor-like transform features and Scatter Orthogonal Fuzzy Neighborhood Discriminant Analysis (SOFNDA) was presented to improve recognition accuracy. Augmented Gabor-like Transform derives desirable facial features to cope with the variation due to illumination and facial expression changes. An efficient feature extraction method named as Scatter Orthogonal Fuzzy Neighborhood Discriminant Analysis (SOFNDA) was developed. By adopting the scatter difference criterion and the removal of null space of total scatter matrix, orthogonal and discriminative features can be extracted efficiently. Extensive experiments have been made to compare the recognition performance of the proposed method with some popular dimensionality reduction methods on Yale and PIE face databases. The results vered the effectiveness of the proposed method. © 2012 ISSN 2185-2766.


Chen Z.,Shanghai JiaoTong University | Cai Y.,Shanghai JiaoTong University | Xu X.,Shanghai JiaoTong University | Xu X.,University of Shanghai for Science and Technology | Xu X.,Shanghai Academy of Systems Science
Chinese Control Conference, CCC | Year: 2012

We present an algorithm of data fusion estimation for dynamic system with multi-sensor and uncertain system models based on Kalman filtering and Interacting Multiple Model. The algorithm estimates the target state using interacting multiple model filtering method after using augmented multi-sensor fusion method. And this method is also available when the system contains different kinds of sensors or the measurement errors of different sensors are related. We test and verify the feasibility of this estimation algorithm through simulation and discuss the effect of the number of sensor on the estimation precision. Results show that, simply increasing the number of sensor cannot always improve the performance of the estimation. Type and number of sensor should be optimized in practical applications. © 2012 Chinese Assoc of Automati.


Liu G.,University of Shanghai for Science and Technology | Liu G.,Shanghai Academy of Systems Science
Advanced Materials Research | Year: 2010

An improved Freeman-Newell functional reasoning model is proposed for the conceptual design of manufacturing process control strategies. The structure in Freeman-Newell model is partitioned into determined subset and undetermined subset. Main framework of the structure is expressed by determined subset. Undetermined subset is presented to express the functions required from next design level. In this way variant design and multi level design reasoning can be supported. Based on the improved Freeman-Newell model, multi level conceptual design methodology for control strategies of manufacturing process is presented. Tracking control algorithm design for a nonlinear manufacturing process plant is provided as the example to verify the design reasoning ability of the improved model. © (2010) Trans Tech Publications.

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