The performance of state-of-art image retrieval systems using Bag-of-Words representation and textual retrieval methods degrades quickly when applied to face images because their local features can not suffer variatio...
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Extracting non-rigid object from images can be used in object recognition, medical image analysis, video monitoring, etc. In order to improve the efficiency and accuracy of visual object extraction, we design a candid...
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Extracting non-rigid object from images can be used in object recognition, medical image analysis, video monitoring, etc. In order to improve the efficiency and accuracy of visual object extraction, we design a candidate shape generator based on a mixture strategy, called mixture generator, it combines the image data driven method with model parameter driven method, and tends to generate valid shape in area which has a high shape prior density value by exploiting the GPDM model, so the efficiency of search is greatly improved. To prove the accuracy of our mixture generator, we have done experiments under the framework of global optimization algorithm (simulated annealing) on the FGNET face database. Experiments show that, compared with traditional ASM algorithm, our method is not only insensitive to initialization conditions, but also can put up with clutters and realize a more robust object extraction.
In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. The joint sparse dictionary consists of positive and negative sub-dictionaries, which model foregroun...
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This paper considers the boundary control of a star-shaped open-channel network modeled by the Saint-Venant equations. We present the boundary feedback stabilization of the Saint-Venant equations by means of a Riemann...
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The convergence speed of multi-agent system is a focused issue in the consensus problem. The traditional consensus algorithm is generally discussed on the single-layer topology. The spectral partitioning algorithm of ...
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In this paper,we present a model predictive control algorithm for input-saturated systems by a saturation-dependent Lyapunov function *** saturation-dependent Lyapunov function captures the real-time information on th...
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ISBN:
(纸本)9781479900305
In this paper,we present a model predictive control algorithm for input-saturated systems by a saturation-dependent Lyapunov function *** saturation-dependent Lyapunov function captures the real-time information on the severity of saturation and thus leads to less conservative results in controller design.A set invariance condition for the systems with input saturation is presented.A min-max MPC algorithm is proposed for the linear parameter-varying(LPV) systems based on the invariant *** MPC controller is determined by solving a linear matrix inequality(LMI) optimization *** example demonstrates the effectiveness of the proposed algorithm.
The problem of how to select a coordinate transformation matrix to improve the LMI conditions for H∞ staticoutput-feedback(SOF) control of discrete-time systems is a challenging open *** paper applies a newly propose...
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ISBN:
(纸本)9781479947249
The problem of how to select a coordinate transformation matrix to improve the LMI conditions for H∞ staticoutput-feedback(SOF) control of discrete-time systems is a challenging open *** paper applies a newly proposed strategy to solve this *** iterative algorithm is developed to produce controllers with locally optimal closed-loop H∞*** algorithm is also applied to other H∞ SOF control problems,such as decentralized H∞ SOF control and simultaneous H∞ SOF ***,numerical examples are provided to demonstrate the effectiveness and advantages of the proposed method.
This paper is concerned with the stability and stabilizability problems of networked controlsystems（NCSs） with partly quantized *** precisely,the remote state variables transported from other sub-systems experience...
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ISBN:
(纸本)9781479900305
This paper is concerned with the stability and stabilizability problems of networked controlsystems（NCSs） with partly quantized *** precisely,the remote state variables transported from other sub-systems experience quantization errors,while the local state variables do *** consideration is much more natural in NCSs due to the distributive nature of *** errors are represented as convex poly-topic *** on the Lyapunov-Krasovskii （L-K） functional approach,sufficient conditions for the existence of a quantized robust Hstate feedback controller for NCSs are *** conditions are obtained in terms of bilinear matrix inequalities（BMIs）.Furthermore,a cone complementarity algorithm is utilized to convert these BMIs into a convex optimization ***,a simulation example is provided to demonstrate the efficiency of proposed theorems.
As one of the most significant characteristics of human cell, subcellular localization plays a critical role for understanding specific functions of mammalian proteins. In this study, we developed a novel computationa...
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The minimum entropy multiple model estimation algorithm(MEMM),one of variable structure multiple model estimators(VSMM),is an effective approach in handling the problems with high mode ***,the performance of MEMM will...
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ISBN:
(纸本)9781479900305
The minimum entropy multiple model estimation algorithm(MEMM),one of variable structure multiple model estimators(VSMM),is an effective approach in handling the problems with high mode ***,the performance of MEMM will deteriorate when the real observation errors are in disaccord with the prior observation error *** this end,we propose the k-means entropy multiple-model estimation algorithm(KMEMM) to refine the model sequence set adaptation ***,the k-means algorithm is employed to make several model sequence ***,the minimum entropy cluster is selected as the best model set and at last the Bayesian estimation is calculated based on *** simulation results demonstrate the efficiency of the proposed algorithm through comparing to several existing algorithms.
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