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Du D.,Information Technology PR | Qi B.,Shanghai University | Fei M.,Shanghai University | Wang Z.,Shanghai University
Information Sciences | Year: 2016

Traditional analysis and design for networked control systems (NCSs) with state quantization have been investigated under single wired/wireless network environment. This paper studies the quantized control of distributed event-triggered NCSs under hybrid wired-wireless networks environment. Unlike the most existing NCSs, the controller communicates with distributed sensors through multiple wired-wireless channels and the measured signals from sensors might suffer from communication constraints of hybrid wired-wireless networks, which makes the quantized control of distributed event-triggered NCSs more complex. To reduce the communication burden of each channel, a distributed event-triggered mechanism and multiple quantization scheme are firstly proposed. The communication characters of hybrid wired-wireless networks are then analyzed, which are described by different Markov chains. Furthermore, a novel system model is presented, and a sufficient condition of the stochastic stability is derived. The relationship between the system stability criteria and the maximum hybrid wired-wireless network-induced delays, the event-generators parameters and multiple quantization parameters is established. Finally, simulation results confirm the effectiveness and feasibility of the proposed method. © 2016 Elsevier Inc. Source


Xiang L.,Jiangnan University | Xie L.,Jiangnan University | Liao Y.,Information Technology PR | Ding R.,Jiangnan University
Mathematical and Computer Modelling | Year: 2010

This paper presents an auxiliary model based hierarchical least squares algorithm to estimate the parameters of single-input multi-output system modelling by combining the auxiliary model identification idea and the hierarchical identification principle. A numerical example is given to show the performance of the proposed algorithm. © 2010 Elsevier Ltd. Source


Stepanov O.A.,Information Technology PR | Vasilyev V.A.,Concern CSRI Elektropribor
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2014

The recurrence algorithms for the Cramer-Rao lower bound for a discrete-time nonlinear filtering problem in the conditions when a forcing noise, measurement errors and initial covariance matrix depend on the state vector to be estimated are derived. It is assumed that the state vector being estimated includes a subvector of time-invariant unknown parameters. Some examples are given to illustrate the applicability of the algorithms obtained. © IFAC. Source


Lebedev A.A.,Joffe Physical Technical Institute | Bulat P.V.,Information Technology PR
Life Science Journal | Year: 2014

Analysis of the national and foreign publications dedicated to the graphene production, its properties study and graphene-based device prototyping. It is demonstrated that one of the most attractive devices for practical realization is a gas sensor based on the graphene film. Also it is demonstrated that a method of silicon carbide thermal decomposition is the advanced technology for the graphene electronics realization. Source


Shen F.,University of Electronic Science and Technology of China | Shen C.,University of Adelaide | Zhou X.,University of Electronic Science and Technology of China | Yang Y.,University of Electronic Science and Technology of China | Shen H.T.,Information Technology PR
Pattern Recognition | Year: 2016

We propose a very simple, efficient yet surprisingly effective feature extraction method for face recognition (about 20 lines of Matlab codes), which is mainly inspired by spatial pyramid pooling in generic image classification. We show that, coupled with a linear classifier, features formed by simply pooling local patches over a multi-level pyramid can achieve state-of-the-art performance on face recognition. The simplicity of our feature extraction procedure is demonstrated by the fact that no learning is involved (except PCA whitening). It is shown that multi-level spatial pooling and dense extraction of multi-scale patches play critical roles in face image classification. The extracted facial features can capture strong structural information of individual faces with no label information being used. We also find that pre-processing on local image patches such as contrast normalization can have an important impact on the classification accuracy. In particular, on the challenging face recognition datasets of FERET and LFW-a, our method improves previous best results by large gaps. Promising results are also achieved on the general image classification database Caltech-101. © 2016 Elsevier Ltd. Source

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