Synchronization in pth Moment for Stochastic Chaotic Neural Networks with Finite-Time Control by Yuhua Xu, Jinmeng Wang, Wuneng Zhou, Xin Wang

“…Finite-time synchronization in pth moment is considered for time varying stochastic chaotic neural networks. Compared with some existing results about finite-time mean square stability of stochastic neural network, we obtain some useful criteria of finite-time synchronization in pth moment for chaotic neural networks based on finite-time nonlinear feedback control and finite-time adaptive feedback control, which are efficient and easy to implement in practical applications. …”
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Investigation of multi-input convolutional neural networks for the prediction of particleboard mechanical properties by Shuoye Chen, Shunsuke Sakai, Miyuki Matsuo-Ueda, Kenji Umemura

Subjects: “…Convolutional neural network…”
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Modeling and Simulation of Real Estate Valuation Based on Genetic Neural Network Model by Shuli Shen

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Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling by Changjin Xu, Peiluan Li

“…A delayed neural network model of two neurons with inertial coupling is dealt with in this paper. …”
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Sustainability metrics targeted optimization and electric discharge process modelling by neural networks by Muhammad Sana, Muhammad Asad, Muhammad Umar Farooq, Mehdi Tlija, Rodolfo Haber

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Almost Sure Stability of Stochastic Neural Networks with Time Delays in the Leakage Terms by Mingzhu Song, Quanxin Zhu, Hongwei Zhou

“…The stability issue is investigated for a class of stochastic neural networks with time delays in the leakage terms. …”
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Nonparametric analysis of inter‐individual relations using an attention‐based neural network by Takashi Morita, Aru Toyoda, Seitaro Aisu, Akihisa Kaneko, Naoko Suda‐Hashimoto, Ikuma Adachi, Ikki Matsuda, Hiroki Koda

“…The flexibility of the neural network would also allow for its application to a wide variety of data with interacting components, such as vocal communication. ​…”
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Decoding Gestures in Electromyography: Spatiotemporal Graph Neural Networks for Generalizable and Interpretable Classification by Hunmin Lee, Ming Jiang, Jinhui Yang, Zhi Yang, Qi Zhao

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LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays by Hui Xu, Ranchao Wu

“…In the current paper, a discrete model of continuous-time neural networks with variable and distributed delays is investigated. …”
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Optimizing photovoltaic power plant forecasting with dynamic neural network structure refinement by Dácil Díaz-Bello, Carlos Vargas-Salgado, Manuel Alcazar-Ortega, David Alfonso-Solar

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Multistability and Instability of Competitive Neural Networks with Mexican-Hat-Type Activation Functions by Xiaobing Nie, Jinde Cao, Shumin Fei

“…We investigate the existence and dynamical behaviors of multiple equilibria for competitive neural networks with a class of general Mexican-hat-type activation functions. …”
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Convergence of Batch Split-Complex Backpropagation Algorithm for Complex-Valued Neural Networks by Huisheng Zhang, Chao Zhang, Wei Wu

“…The batch split-complex backpropagation (BSCBP) algorithm for training complex-valued neural networks is considered. For constant learning rate, it is proved that the error function of BSCBP algorithm is monotone during the training iteration process, and the gradient of the error function tends to zero. …”
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Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management by Zhuojie Li

“…According to the BP neural network algorithm, for the problem that the input variables of the BP network cannot be automatically optimized during the modeling process of the multivariable complex system, it is used to establish a neural network optimization algorithm according to the gray correlation analysis (GM2 BPANN). …”
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Spatial-Temporal Fusion Graph Neural Networks With Mixed Adjacency for Weather Forecasting by Ang Guo, Yanghe Liu, Shiyu Shao, Xiaowei Shi, Zhenni Feng

“…., recurrent neutral networks and graph neural networks, have been proposed for weather forecasting. …”
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Dual Convolution Neural Networks of Ensemble Learning with Attention Mechanism for Rice Classification by Cheng Linfeng

“…The aim of this project is to develop a dual convolutional neural network for ensemble learning based on the initial model and the res network model, and apply the ensemble model to the rice classification problem. …”
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Equalizer Design: HBOA-DE-trained radial basis function neural networks by Santosh Kumar Das, Satya Ranjan Pattanaik, Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Abdulaziz S. Almazyad, Muhammed Basheer Jasser, Guojiang Xiong, Ali Wagdy Mohamed

“…Based on a suitable network topology and transfer function, the presented work proposes an algorithm for training radial basis function neural networks (RBFNNs) that is applied to the problem of channel equalization. …”
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Offline English Handwritten Character Recognition using Sequential Convolutional Neural Network by Muhammad Iqbal, Muniba Humayun, Raheel Siddiqi, Christopher J. Harrison, Muneeb Abid Malik

“…This research paper proposes a deep learning convolutional neural network that is tested and compared with renowned pre-trained models using transfer learning. …”
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Customer Churn Modeling via the Grey Wolf Optimizer and Ensemble Neural Networks by Maryam Rahmaty, Amir Daneshvar, Fariba Salahi, Maryam Ebrahimi, Adel Pourghader Chobar

“…This study proposes a hybrid system based on fuzzy entropy criterion selection algorithm with similar classifiers, grey wolf optimization algorithm, and artificial neural network to predict the customer churn of those companies that suffer losses from losing customers over time. …”
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Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays by Yanke Du, Rui Xu

“…A class of interval neural networks with time-varying delays and distributed delays is investigated. …”
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Research on the Prediction of the Water Demand of Construction Engineering Based on the BP Neural Network by Hao Peng, Han Wu, Junwu Wang

“…However, the errors of the BP neural network model, the BP neural network improved by genetic algorithm, and the pluralistic return were larger. …”
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