The use of modern information technologies in the training of mature specialists accelerates the process of training specialists. One of the ways to achieve the main goal is to create and improve the computer adaptive...
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In view of the problems that the current attitude measurement method of rotating projectile based on three-axis infrared needs to normalize the sensor according to the surrounding environment in advance, resulting in ...
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Aiming to address the low processing efficiency problem that arises with the massive image data generated in tobacco-related commercial terminals, a deep learning technology-based laser code text recognition solution ...
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To enhance the disturbance rejection of morphing aircraft, an adaptive backstepping control method based on the RBF neural network is proposed. Firstly, the aerodynamic parameters and model parameters are modeled as f...
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By introducing inter-satellite link, Multifunction Test Sat and Tiantuo 5 can realize functions such as cooperative positioning, formation control and distributed computing. In order to reduce the construction and dev...
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This paper presents a new approach to accelerate large-scale bundle adjustment (BA). As starting point, we empirically demonstrate that there exist a significant amount of redundant information that has yet to be leve...
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In recent years, image processing based on stochastic resonance has received more and more attention. In this paper, a dynamic saturated nonlinear stochastic pooling network model based on adaptive stochastic resonanc...
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An innovative adaptive power management control strategy has been developed and leveraged in a lithium-ion battery (LiB)/lithium-ion supercapacitor (LiC) hybrid power system. The hybrid system pairs both energy densit...
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Image analysis in scenes with low contrast in the infrared is difficult in general. At sea, this can be further challenging due to varying levels of sea clutter. Ideally, adaptive algorithms should be able to consider...
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The paper considered the problem of applying neural network technologies to detect signals in conditions of complex non-Gaussian disturbances with a priori uncertainty of probability distributions. In particular, the ...
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