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Zeyu Xu, Wenbin Yu, Chengjun Zhang and Yadang Chen
In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic collaboration between quantum and classical computing models has emerged as a promising solution for tackling complex computational challenges. Long short-term memory (LSTM)...
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Hermilo Santiago-Benito , Diana-Margarita Córdova-Esparza , Noé-Alejandro Castro-Sánchez , Teresa García-Ramirez , Julio-Alejandro Romero-González and Juan Terven
This paper introduces a novel method for collecting and translating texts from the Mixtec to the Spanish language. The method comprises four primary steps. First, we collected a Mixtec?Spanish corpus that includes 4568 sentences from educational and reli...
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Min Xu, Wenjie Tian and Xiangpeng Zhang
The three-degrees-of-freedom (3-DOF) parallel robot is commonly employed as a shipborne stabilized platform for real-time compensation of ship disturbances. Pose accuracy is one of its most critical performance indicators. Currently, neural networks have...
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Anni Zhao, Arash Toudeshki, Reza Ehsani, Joshua H. Viers and Jian-Qiao Sun
The Delta robot is an over-actuated parallel robot with highly nonlinear kinematics and dynamics. Designing the control for a Delta robot to carry out various operations is a challenging task. Various advanced control algorithms, such as adaptive control...
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Mingwei Zhao, Xiaoxiao Ju, Ni Wang, Chun Wang, Weibo Zeng and Yan Xu
Extracting a channel network based on the Digital Elevation Model (DEM) is one of the key research topics in digital terrain analysis. However, when the channel area is wide and flat, it is easy to form parallel channels, which seriously affect the accur...
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Michiel van der Vlag, Lionel Kusch, Alain Destexhe, Viktor Jirsa, Sandra Diaz-Pier and Jennifer S. Goldman
Global neural dynamics emerge from multi-scale brain structures, with nodes dynamically communicating to form transient ensembles that may represent neural information. Neural activity can be measured empirically at scales spanning proteins and subcellul...
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Felipe C. Farias, Teresa B. Ludermir and Carmelo J. A. Bastos-Filho
In this paper we propose a procedure to enable the training of several independent Multilayer Perceptron Neural Networks with a different number of neurons and activation functions in parallel (ParallelMLPs) by exploring the principle of locality and par...
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Sirui Shen, Daobin Zhang, Shuchao Li, Pengcheng Dong, Qing Liu, Xiaoyu Li and Zequn Zhang
Heterogeneous graph neural networks (HGNNs) deliver the powerful capability to model many complex systems in real-world scenarios by embedding rich structural and semantic information of a heterogeneous graph into low-dimensional representations. However...
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Jin Peng, Chengming Liu, Haibo Pang, Xiaomeng Gao, Guozhen Cheng and Bing Hao
With the rise of image manipulation techniques, an increasing number of individuals find it easy to manipulate image content. Undoubtedly, this presents a significant challenge to the integrity of multimedia data, thereby fueling the advancement of image...
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Aleksandr Cariow, Janusz P. Paplinski and Marta Makowska
The paper introduces a range of efficient algorithmic solutions for implementing the fundamental filtering operation in convolutional layers of convolutional neural networks on fully parallel hardware. Specifically, these operations involve computing M i...
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