This paper investigates the asymptotical stability for discrete-time Cohen-Grossberg neural networks with both timevarying and distributed delays. By constructing a novel Lyapunov-Krasovskii functional and introducing...
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This paper investigates the asymptotical stability for discrete-time Cohen-Grossberg neural networks with both timevarying and distributed delays. By constructing a novel Lyapunov-Krasovskii functional and introducing some free-weighting matrices, one delay-dependent sufficient condition is obtained by using convex combination. The criterion is presented in terms of LMIs and the feasibility can be easily checked with the help of LMI in Matlab Toolbox. In addition, the activation function can be described more generally, which generalizes those earlier methods. Finally, the effectiveness of obtained results can be further illustrated by one numerical example in comparison with the existent ones.
Knowledge manufacturing system has the ability of modifying dynamically manufacturing mode rapidly when production environment factors change. It is essential to evaluate the matching degree of established manufacturi...
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ISBN:
(纸本)9781424494408
Knowledge manufacturing system has the ability of modifying dynamically manufacturing mode rapidly when production environment factors change. It is essential to evaluate the matching degree of established manufacturing mode and changed production environment factors. In this paper, a matching decision model for self-adaptability of knowledge manufacturing system based on the fuzzy neural network is proposed. The changed production environment factors are regarded as linguistic variable inputs. A modified momentum factor B-P algorithm consisting of information feed-forward process and the error back-propagation process is used. The proposed FNN model is employed to evaluate the matching degree of a car-lamp production manufacturing mode to variable environment units. Matching result indicates adaptive degree of manufacturing system. Experiment result demonstrates the method is effective.
As the number of vehicles in the monitoring system increases, the size of the table for storing their past data becomes very large, which brings performance troubles occurred in the systems with VLDB. To improve the d...
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ISBN:
(纸本)9781612847719
As the number of vehicles in the monitoring system increases, the size of the table for storing their past data becomes very large, which brings performance troubles occurred in the systems with VLDB. To improve the data-access efficiency and keep the database stability, the original table is proposed to be partitioned. According to the functional requirements for database from the vehicle monitoring system, the range partition is suggested, with twelve partitions for one year's historical data and each partition corresponding to a separate month. Then the partitioned table is created after finishing the definitions of the partitioning function and the partitioning schema, where the former gives a rule for partitioning and the latter specifies the storage places of partitions to different file groups. Because the data in the partitioned table is separated into several file groups, the data-access is capable of parallel processing and keeps a higher efficiency. Tests show that the partitioned table works in improving the database performance and the query time is greatly redu.ed compared to that cost in the original table.
In this paper, some improved results on the state estimation problem for recurrent neural networks with both time-varying and distributed time-varying delays are presented. Through available output measurements, an im...
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In this paper, some improved results on the state estimation problem for recurrent neural networks with both time-varying and distributed time-varying delays are presented. Through available output measurements, an improved delay-dependent criterion is established to estimate the neuron states such that the dynamics of the estimation error is globally exponentially stable, and the derivative of time-delay being less than 1 is removed, which generalize the existent methods. Finally, two illustrative examples are given to demonstrate the effectiveness of the proposed results.
In this paper,an improved mean-square exponential stability condition and delayed-state-feedback controller for stochastic Markovian jump systems with mode-dependent time-varying state delays are obtained. First,by co...
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In this paper,an improved mean-square exponential stability condition and delayed-state-feedback controller for stochastic Markovian jump systems with mode-dependent time-varying state delays are obtained. First,by constructing a modified Lyapunov-Krasovskii functional,a mean-square exponential stability condition for the above systems is presented in terms of linear matrix inequalities (LMIs). Here,the decay rate can be a finite positive constant in a range and the derivative of time-varying delays is only required to have an upper bound which is not required to be less than 1. Then,based on the proposed stability condition,a delayed-state-feedback controller is designed. Finally,numerical examples are presented to illustrate the effectiveness of the theoretical results.
This paper investigates the problem of robust exponential admissibility for a class of continuous-time uncertain switched singular systems with interval time-varying delay. By defining a properly constructed decay-rat...
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This paper investigates the problem of robust exponential admissibility for a class of continuous-time uncertain switched singular systems with interval time-varying delay. By defining a properly constructed decay-rate-dependent Lyapunov function and the average dwell time approach, a delay-range-dependent sufficient condition is derived for the nominal system to be regular, impulse free, and exponentially stable. This condition is also extended to uncertain case. The obtained results provide a solution to one of the basic problems in continuous-time switched singular time-delay systems, that is, to identify a switching signal for which the switched singular time-delay system is regular, impulse free, and exponentially stable. Numerical examples are given to demonstrate the effectiveness of the obtained results.
The classical mean shift tracking algorithm is apt to make errors or lose the target if the target is occluded for a very long time. Thus an improved mean shift tracking algorithm is proposed. This algorithm divides t...
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The classical mean shift tracking algorithm is apt to make errors or lose the target if the target is occluded for a very long time. Thus an improved mean shift tracking algorithm is proposed. This algorithm divides the target into multiple fragments and integrates spatial information by using different weights of each image fragment. The similarity coefficient between target template and candidate template consists of the Bhattacharyya coefficients of the corresponding multiple fragments. Experimental results show that the proposed method is efficient when the target is occluded for a long time. A new method named edge-histogram is used. This method is based on original scale updating mechanism and make a further judgment that whether the target is smaller or not by calculating the Bhattacharyya coefficient between the target's edge-histograms of the current frame and the previous one. Experimental results show that the proposed algorithm can deal with the scale problem very well.
According to the functions of database required by the vehicle monitoring system, three entities, including the vehicle, the vehicle terminal and the user, and their relationships are created and described by an entit...
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According to the functions of database required by the vehicle monitoring system, three entities, including the vehicle, the vehicle terminal and the user, and their relationships are created and described by an entity-relationship (E-R) diagram for the database concept design. The database logical model is built. In order to improve the performance of the database application, three kinds of optimization are proposed in different aspects. First, to improve the low efficiency of data accessing caused by a huge table, multiple sub-tables are divided from the original huge table by a distributed storage solution, which greatly increases the storage capability of the database based on decentralized management. Secondly, zoning optimizations are made for the single tables with a large amount of data. Due to the parallel processing for data, a good performance can be obtained even when the data accessing is frequent. Finally, the query speed of a specific table is improved by making fair use of the clustered index under the guide of different application purposes. Performance of the database in an actual vehicle monitoring system is evaluated. The results show that the optimized database can timely respond the real-time requests of data accessing. It is powerful for data storage and management, which ensures the stability and reliability of the system performance.
An adaptive threshold segmentation algorithm based on HS joint statistics using HSI color model is introduced in order to improve the performance of image segmentation and the robustness of object recognition to illum...
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An adaptive threshold segmentation algorithm based on HS joint statistics using HSI color model is introduced in order to improve the performance of image segmentation and the robustness of object recognition to illumination change. Statistics of H and S component value of all the pixels in the region of interest (ROI) is obtained after image segmentation in HSI color space. The changing rule of statistics is verified while an empirical scale factor is applied to reflect the difference between the influence of H value and S value on segmentation threshold. The threshold is thus adjusted online according to the proposed approach. Experimental results demonstrate the decrease trend of H and S component value with intensified light. Furthermore, it validates the robustness of the approach under the circumstance of changing illumination. Thus the accuracy of the vision-based robot grasping is significantly improved.
In order to solve the problems of inaccurate positioning in current vehicle monitoring systems, an intelligent vehicle monitoring system based on mobile video and WebGIS (Web geographic information system) is proposed...
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In order to solve the problems of inaccurate positioning in current vehicle monitoring systems, an intelligent vehicle monitoring system based on mobile video and WebGIS (Web geographic information system) is proposed and designed. The system is composed of front-end equipment, system platform and client. The instant image information captured by vehicle mobile video and the GPS(global positioning system) positioning location information received by the terminal are transmitted from front-end to system platform via the GPRS(general packet radio service) mobile communications platform. Also, a highly compressed digital video and audio codec technology standard named H.264/AVC is employed to compress the real-time mobile video information and the Google Maps API is called to display the current position of vehicles on the electronic map. Furthermore, the spatial analysis capabilities of GIS plus the GPS information not only make tracking feasibly, but also provide aid in decision making. It is shown that the system can not only reproduce the video data timely and accurately, but also accurately position the mobile vehicles so as to provide a better service in monitoring, control, management, analysis, decision-making and command functions, which expands the application fields and development prospects of WebGIS and mobile video monitoring technology.
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