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Gaoyuan Cai, Juhu Li, Xuanxin Liu, Zhibo Chen and Haiyan Zhang
Recently, the deep neural network (DNN) has become one of the most advanced and powerful methods used in classification tasks. However, the cost of DNN models is sometimes considerable due to the huge sets of parameters. Therefore, it is necessary to com...
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Ferenc Izsák and Taki Eddine Djebbar
We propose neural-network-based algorithms for the numerical solution of boundary-value problems for the Laplace equation. Such a numerical solution is inherently mesh-free, and in the approximation process, stochastic algorithms are employed. The chief ...
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Sihmehmet Yildiz, Hayriye Pehlivan Solak and Melike Nikbay
Uncertainty quantification has proven to be an indispensable study for enhancing reliability and robustness of engineering systems in the early design phase. Single and multi-fidelity surrogate modelling methods have been used to replace the expensive hi...
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Prateek Saurabh Srivastav, Lan Chen and Arfan Haider Wahla
Channel estimation is a formidable challenge in mmWave Multiple Input Multiple Output (MIMO) systems due to the large number of antennas. Therefore, compressed sensing (CS) techniques are used to exploit channel sparsity at mmWave frequencies to calculat...
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Alexey V. Setukha,Vladimir A. Aparinov,Andrey A. Aparinov
Pág. 121 - 125
In this article the authors present parallel implementation of numerical method for computer modeling of dynamics of a parachute with filled canopy. To solve the 3D problem of parachute free motion numerically, authors formulate tied problem of dynamics ...
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