Results 11 to 20 of about 92,534 (217)
CAAI Transactions on Intelligence Technology, 2023 Manipulators actuate joints to let end effectors to perform precise path tracking tasks. Recurrent neural network which is described by dynamic models with parallel processing capability, is a powerful tool for kinematic control of manipulators.
Zhan Li, Shuai Li
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Deductron—A Recurrent Neural Network
Frontiers in Applied Mathematics and Statistics, 2020 The current paper is a study in Recurrent Neural Networks (RNN), motivated by the lack of examples simple enough so that they can be thoroughly understood theoretically, but complex enough to be realistic.
Marek Rychlik
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Effect of Bodybuilding and Fitness Exercise on Physical Fitness Based on Deep Learning
Emergency Medicine International, 2022 With the rapid development of society and economy, people’s living standards are improving day by day, and increasingly attention is paid to physical health, which has set off a fitness upsurge.
Manman Sun, Lijun Wang
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An attractor-based complexity measurement for Boolean recurrent neural networks. [PDF]
PLoS ONE, 2014 We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics.
Jérémie Cabessa, Alessandro E P Villa
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Comparison of Neural Network and Recurrent Neural Network to Predict Rice Productivity in East Java
JITeCS (Journal of Information Technology and Computer Science), 2021 Rice is the staple food for most of the population in Indonesia which is processed from rice plants. To meet the needs and food security in Indonesia, a prediction is required.
Andi Hamdianah +2 more
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Recurrent neural network wave functions
Physical Review Research, 2020 A core technology that has emerged from the artificial intelligence revolution is the recurrent neural network (RNN). Its unique sequence-based architecture provides a tractable likelihood estimate with stable training paradigms, a combination that has ...
Mohamed Hibat-Allah +4 more
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General Recurrent Neural Network for Solving Generalized Linear Matrix Equation
Complexity, 2017 This brief proposes a general framework of the nonlinear recurrent neural network for solving online the generalized linear matrix equation (GLME) with global convergence property. If the linear activation function is utilized, the neural state matrix of
Zhan Li, Hong Cheng, Hongliang Guo
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Clustering Based on Continuous Hopfield Network
Mathematics, 2022 Clustering aims to group n data samples into k clusters. In this paper, we reformulate the clustering problem into an integer optimization problem and propose a recurrent neural network with n×k neurons to solve it. We prove the stability and convergence
Yao Xiao +3 more
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Sensors, 2021 In this study, a scheme of remaining useful lifetime (RUL) prognosis from raw acoustic emission (AE) data is presented to predict the concrete structure’s failure before its occurrence, thus possibly prolong its service life and minimizing the risk of ...
Tuan-Khai Nguyen +2 more
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Detection of Shoplifting on Video Using a Hybrid Network
Computation, 2022 Shoplifting is a major problem for shop owners and many other parties, including the police. Video surveillance generates huge amounts of information that staff cannot process in real time.
Lyudmyla Kirichenko +3 more
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