The lag quasi-synchronization of nonlinear coupled networks with time-varying delay in the presence of parameter mismatches by using aperiodically intermittent pinning control is investigated in this *** paper has two...
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ISBN:
(纸本)9781479970186
The lag quasi-synchronization of nonlinear coupled networks with time-varying delay in the presence of parameter mismatches by using aperiodically intermittent pinning control is investigated in this *** paper has two main differences with previous works:one is that the type of the intermittent pinning control is aperiodic while that in previous works is periodic;the other is that the coupling function we choose is *** utilizing the aperiodically intermittent pinning control idea,we pin the coupled networks by a simple controller to achieve the lag *** sufficient criteria are obtained to guarantee lag *** last,some simulations are presented to verify the correctness of the obtained theoretical results.
Analysis approaches of liveness are important to Petri nets theory,but the relevant research work in the past is still *** paper proposed a new modified reachability graph(NMRG) approach for liveness analysis of ω-in...
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Analysis approaches of liveness are important to Petri nets theory,but the relevant research work in the past is still *** paper proposed a new modified reachability graph(NMRG) approach for liveness analysis of ω-independent Petri *** NMRG of a Petri net is transformed from its NMRT and can be used to analyze liveness and deadlock of ω-independent unbound Petri nets.A sufficient condition of liveness and a sufficient and necessary condition of deadlock of ω-independent Petri nets are proposed on the basis of *** are given to illustrate the method.
In this paper, a new method is proposed to evaluate the performance of concurrent systems. A concurrent system consisting of multiple processes that communicate via message passing mechanisms is modeled by a Petri net...
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This study was designed to develop solutions for facial action human computer interaction on embedded devices. This paper presents a new facial detection algorithm using dimension reduction and regionalization computi...
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ISBN:
(纸本)9781467374439
This study was designed to develop solutions for facial action human computer interaction on embedded devices. This paper presents a new facial detection algorithm using dimension reduction and regionalization computing. Then, a dynamic action judgement algorithm based on simplified Facial Expression Coding system is proposed to describe human facial action. This paper also provide the facial action capture system ***, an accuracy report is presented to validate the usefulness of system.
Lane detection based on computer vision is a key technology of Automatic Drive system for intelligent vehicles. In this paper, we propose a real-time and efficient lane detection algorithm that can detect lanes appear...
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ISBN:
(纸本)9781479982622
Lane detection based on computer vision is a key technology of Automatic Drive system for intelligent vehicles. In this paper, we propose a real-time and efficient lane detection algorithm that can detect lanes appearing in urban streets and highway roads under complex background. In order to enhance lane boundary information and to be suitable for various light conditions, we adopt canny algorithm for edge detection to get good feature points. We use the generalized curve lane parameter model, which can describe both straight and curved lanes. We propose an improved random sample consensus (RANSAC) algorithm combined with the least squares technique to estimate lane model parameters based on feature extraction. Experiments are conducted on both real road lane videos captured by Tongji University and Caltech Lane Datasets. The experimental results show that our algorithm is can meet the real time requirement and fit lane boundaries well in various challenging road conditions.
In the field of identity authentication, existing researches on user keystroke authentication only focus on the situation in which a single user uses a single account. When multiple users share one account, there emer...
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The personalized recommendation systems could better improve the personalized service for network user and alleviate the problem of information overload in the Internet. As we all know, the key point of being a succes...
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In the process of electronic transaction, there are many abnormal conditions such as user's own mistakes, account theft and so on. Inspired by mechanisms of immune homeostasis, immune surveillance and immune updat...
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The paper focuses on a stabilizing controller design problem for networked systems with quantization,mixed delays,and a series of packet losses due to the signal transmission through the unreliable communication *** o...
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The paper focuses on a stabilizing controller design problem for networked systems with quantization,mixed delays,and a series of packet losses due to the signal transmission through the unreliable communication *** of both sensor-to-controller and controller-to-actuator are taken into account for the networked systems,and the distributed time delay is also considered in the network *** conditions for designing the controller as well as the system parameters can be obtained by solving certain linear matrix ***,the effectiveness of the designed method is proved by a numerical example.
This paper introduces a regularization method called Correlative Filter (CF) for Convolutional Neural Network (CNN), which takes advantage of the relevance between the convolutional kernels belonging to the same convo...
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ISBN:
(纸本)9781479986989
This paper introduces a regularization method called Correlative Filter (CF) for Convolutional Neural Network (CNN), which takes advantage of the relevance between the convolutional kernels belonging to the same convolutional layer. During the process of training with the proposed CF method, several pairs of filters are designed in a manner of randomness to contain opposite weights in low-level layers. Regarding higher level layers where synthetical features are processed, the relation between correlative filters is explored as translation of various directions. The proposed CF method attempts to optimize the inner structure of convolutional layers and it can work jointly with other regularization techniques, such as stochastic pooling, Dropout, etc. The experimental results on the competitive image classification benchmark dataset CIFAR-10 demonstrates the performance of the proposed CF method, additionally, it is also verified that the proposed CF method is wonderful to be employed to enhance several state-of-the-art regularization models.
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