Robust H∞ control of a class of discret-time uncertain systems is discussed which contains linear nominal parts and norm-bounded nonlinear uncertainties in both state and output equations. Such systems have a unique ...
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Robust H∞ control of a class of discret-time uncertain systems is discussed which contains linear nominal parts and norm-bounded nonlinear uncertainties in both state and output equations. Such systems have a unique characteristic, that is, the two norm-bounded nonlinear uncertainties have the equivalent representation by means of time-varying and norm-bounded linear uncertainties. The two nonlinear uncertainty sets are considered to be different. Then, by converting such systems into related discrete-time linear systems with time-varying and norm-bounded linear uncertainties, it is obtained that a sufficient condition for robust H∞ control of such systems is equivalent to the solvability of the same problem of the related linear uncertain systems, which is solvable by means of a linear algebraic Riccati inequality.
This paper addresses the use of deep learning techniques in 3D point cloud labeling of environment representations for the task of a semantic visual localization of mobile robots. In contrast to standard problems reso...
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This paper addresses the use of deep learning techniques in 3D point cloud labeling of environment representations for the task of a semantic visual localization of mobile robots. In contrast to standard problems reso...
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ISBN:
(数字)9781665466929
ISBN:
(纸本)9781665466936
This paper addresses the use of deep learning techniques in 3D point cloud labeling of environment representations for the task of a semantic visual localization of mobile robots. In contrast to standard problems resolved with Convolutional Neural Networks (CNNs), the paper deals with applying CNNs to segment point clouds that are, unlike images, unordered and unstructured. The used point clouds contain laser measurements of 3D positions (x,y,z) as well as captured RGB camera images from the scanned scene to colorize the point cloud (RGB values). The main focus of the paper is on implementation and evaluation of a hand-crafted convolution layer and the ConvPoint CNN architecture that introduces continuous convolutions for point cloud processing. The solution was implemented in the Python programming language using the PyTorch deep learning framework.
Epilepsy is a serious chronic neurological disorder and it can be detected by analyzing an Electroencephalogram acquired from non-invasive methods. Different strategies have been used for the identification of frequen...
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Synchronization plays an important role in telecommunication systems and integrated circuits. The Master-Slave is a commonly used strategy for clock signal distribution. However, due to the wireless networks developme...
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