In this paper we consider the problem of sensor scheduling for distributed estimation with power constraint. To satisfy the requirement of energy consumption, we assume that each sensor sends data to its adjacent sens...
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ISBN:
(纸本)9781479978878
In this paper we consider the problem of sensor scheduling for distributed estimation with power constraint. To satisfy the requirement of energy consumption, we assume that each sensor sends data to its adjacent sensors with a given probability, where the state of the system is estimated by means of distributed estimators. First, we design optimal estimator gain to minimize the estimation error covariance for each sensor, and then we find an upper bound of the expected state error covariance, provide a sufficient condition to guarantee the stability of the proposed estimator. To find the optimal communication probability, we further formulate the sensor scheduling problem as an optimization problem, which is relaxed to a convex optimization in the form of LMIs.
In the literatures, to design state feedback controller to partially stabilize Boolean control network is rarely *** by this, this paper studies partial stabilization for Boolean network with state feedback control. A...
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ISBN:
(纸本)9781467374439
In the literatures, to design state feedback controller to partially stabilize Boolean control network is rarely *** by this, this paper studies partial stabilization for Boolean network with state feedback control. A sufficient condition for the existence of a state feedback controller to achieve the partial stabilization is established first. Then, the feedback control law is proposed. Finally, examples are presented to show the proposed design procedure.
In the field of video surveillance, adaptive Gaussian mixture model (GMM) is widely used as the background-pixel dynamic modeling approach. GMM produced each pixel Gaussian distribution corresponds to the respective, ...
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In the field of video surveillance, adaptive Gaussian mixture model (GMM) is widely used as the background-pixel dynamic modeling approach. GMM produced each pixel Gaussian distribution corresponds to the respective, but this ignores the impact of the movement of the object itself. The ideas of object kinematic model is presented to guide the number of distribution in the process of iterative, which can speed up the process of clustering, and the results indicate that this method can improve the efficiency and stability of background modeling.
This paper recalls a novel data-driven model-free adaptive control (MFAC) method for a class of interconnected discrete-time nonlinear systems, whose model is unavailable and interactions between each subsystem are me...
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ISBN:
(纸本)9781479978632
This paper recalls a novel data-driven model-free adaptive control (MFAC) method for a class of interconnected discrete-time nonlinear systems, whose model is unavailable and interactions between each subsystem are measurable. Then, under some mild conditions, stability of the closed-loop system is analyzed theoretically. Compared with original MFAC, the proposed MFAC for interconnected systems belongs to decentralized control method, and makes full use of the interacted data to achieve better performance. The effectiveness and superiority are verified by simulation result.
The gaze-independent brain-computer interface (BCI) based on rapid serial visual presentation (RSVP) is an extension of the oddball paradigm, and can facilitate communication for people with severe neuromuscular disor...
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The gaze-independent brain-computer interface (BCI) based on rapid serial visual presentation (RSVP) is an extension of the oddball paradigm, and can facilitate communication for people with severe neuromuscular disorders. Recently, some researches showed that the gaze-independent BCIs based on RSVP used dummy face pictures as stimuli obtained high performance. However, the user' fatigue wasn't be fully considered. Therefore, it is necessary to reduce users' fatigue and to further improve the performance of them. Some studies suggested that face elicited high event related potential (ERP) were mediated by the eye region. That is, face with only eyes region could evoke as high ERPs as completed face. In this paper, an improved paradigm was presented which used dummy face with only eyes region as stimulus. Ten healthy subjects participated in our experiment. Compared with the complete dummy face stimulus, the results showed that the dummy face with only eyes region stimulus could evoke higher N200 and VPP amplitudes. Results from users' feedback also showed the dummy face with only eyes region pattern made them more relaxed.
Problem statement: The aim of this study was to find the empirical model that describes the growth kinetics of Dunaliella salina, with low production cost and to estimate parameters of this model. Approach: In this st...
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This paper considers the distributed estimation of an unstable target via constant-gain estimators under local communications and channel fading. The communication graph is assumed to be fixed and undirected, and the ...
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Health, Safety and Environment management system (HSE) is a general management system of international oil and gas industry. In order to comply with HSE management system, an air quality monitoring system is researche...
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Health, Safety and Environment management system (HSE) is a general management system of international oil and gas industry. In order to comply with HSE management system, an air quality monitoring system is researched based on ZigBee wireless sensor technology, which is applied in industrial sites. The system includes: detecting terminal, wireless router, wireless gateway, software of field devices and monitoring equipment; the system can measure a variety of gas parameters, such as: CO 2 concentration, CO concentration, air quality level, temperature and humidity; Features of the system have high accuracy, quick sensitivity, wide monitoring range, etc..
This paper is concerned with the H∞ fault detection (FD) for a class of networked systems with random packet losses, sensor saturation and multiplicative noises. The network with both output measurement and control p...
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ISBN:
(纸本)9781467391054
This paper is concerned with the H∞ fault detection (FD) for a class of networked systems with random packet losses, sensor saturation and multiplicative noises. The network with both output measurement and control packet losses is modeled with two independent Bernouli distributed white sequences. H∞ filtering theory is adapted to formulate the problem of fault detection for networked systems. The output measurement is affected by sensor saturation which is described by sector-nonlinearities, and the multiplicative noises are modeled as a form of Gaussian white noise. The purpose of the addressed problem is to design a fault detection filter such that, the fault detection dynamic system is exponentially stable in the mean square, and the error between the residual value and fault value is made as small as possible. A sufficient condition for FD filter is derived by solving the linear matrix inequality (LMI). Finally, a numerical example is illustrated to show the effectiveness of the designed method.
In this paper, the vigilance levels during day time short nap sleep were estimated on the basis of Markov process Amplitude (MPA) EEG model. The ultimate purpose was to adopt the MPA model to discriminate three le...
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In this paper, the vigilance levels during day time short nap sleep were estimated on the basis of Markov process Amplitude (MPA) EEG model. The ultimate purpose was to adopt the MPA model to discriminate three levels of vigilance through a simple neural network. A set of parameters were firstly calculated based on MPA EEG model. Secondly, correlation analysis was adopted to extract effective parameters to ensure a small amount of inputs of the artificial neural network. The outputs of artificial neural network were the classified three levels: wakeful, drowsy and sleep. The obtained estimation result showed that the accuracy of wakeful was about 90.0%, drowsy 80.0%, and sleep 93.3%.
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