This paper investigates the consensus problem for a set of nonlinear multi-agent systems with nonlinear interconnections. First, in order to reduce the communication burden in the multi-agent network, a distributed ev...
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ISBN:
(纸本)9781479900305
This paper investigates the consensus problem for a set of nonlinear multi-agent systems with nonlinear interconnections. First, in order to reduce the communication burden in the multi-agent network, a distributed event-triggered consensus control is designed by taking into account the effect of the nonlinear interconnections. Then, based on the Lyapunov functional method and the Kronecker product technique, sufficient conditions are obtained to guarantee the consensus in the form of linear matrix inequality (LMI). Finally, a simulation example is proposed to illustrate the effectiveness of the developed theory.
A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV col...
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A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization(CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods.
While the state-of-the-art speech enhancement methods are focused on the modification of the noisy spectral amplitude, our recent findings demonstrate positive impact of incorporating the speech phase spectrum in spee...
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Visual tracking is a fundamental computer vision task with a wide range of applications. Kernelized Correlation Filter (KCF) is an excellent algorithm with high tracking speed. However, the target tracking scale in th...
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This study investigates the consensus problem of second-order multi-agent systems (MASs) via impulsive control using position-only information with communication delays. The communication delays between any two distin...
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For public security, an intelligent video surveillance system that can analyze large-scale crowd scenes has become an urgent need. In this paper, we propose a system that integrates multiple crowd properties, includin...
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In this paper, a robust homography estimation method is proposed to match multiview images in the uncalibrated case. This method formulates a new loss function to verify homography hypothesis, which combines models of...
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This paper proposes a new second-order continuous-time multi-agent model and analyzes the controllability of second-order multi-agent system with multiple leaders based on the asymmetric *** paper considers the more g...
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This paper proposes a new second-order continuous-time multi-agent model and analyzes the controllability of second-order multi-agent system with multiple leaders based on the asymmetric *** paper considers the more general case:velocity coupling topology is different from location coupling *** sufficient and necessary conditions are presented for the controllability of the system with multiple *** addition,the paper studies the controllability of the system with velocity damping *** results are given to illustrate the correctness of theoretical results.
Semantic segmentation network is able to detect multi-scale traffic sign effectively. However, probabilities that different scale features participate in decision are equal in the network. In this work, we propose a l...
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The task of gland segmentation based on deep learning serves as a crucial auxiliary tool for diagnosing cancer. However, existing methods still exhibit shortcomings in handling gland adhesion and scale adaptability. T...
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