Showing 721 - 740 results of 5,752 for search '"neural networks"', query time: 0.10s Refine Results
  1. 721

    Climate model downscaling in central Asia: a dynamical and a neural network approach by B. Fallah, B. Fallah, M. Rostami, M. Rostami, E. Russo, P. Harder, C. Menz, P. Hoffmann, I. Didovets, F. F. Hattermann, F. F. Hattermann

    Published 2025-01-01
    “…Finally, we train a convolutional neural network (CNN) to map a GCM simulation to its dynamically downscaled CCLM counterpart. …”
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  2. 722

    Real-Time Control Strategy of Elman Neural Network for the Parallel Hybrid Electric Vehicle by Ruijun Liu, Dapai Shi, Chao Ma

    Published 2014-01-01
    “…Through researching the instantaneous control strategy and Elman neural network, the paper established equivalent fuel consumption functions under the charging and discharging conditions of power batteries, deduced the optimal control objective function of instantaneous equivalent consumption, established the instantaneous optimal control model, and designs the Elman neural network controller. …”
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  3. 723
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    Synchronization in Finite Time of Fuzzy Neural Networks with Hybrid Delays and Uncertain Nonlinear Perturbations by Shuyue Zhao, Kelin Li, Weiyi Hu

    Published 2022-01-01
    “…This paper deals with the finite-time synchronization problem of a class of fuzzy neural networks with hybrid delays and uncertain nonlinear perturbations. …”
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  6. 726
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    Centralized and Decentralized Data-Sampling Principles for Outer-Synchronization of Fractional-Order Neural Networks by Jin-E Zhang

    Published 2017-01-01
    “…This paper aims to investigate the outer-synchronization of fractional-order neural networks. Using centralized and decentralized data-sampling principles and the theory of fractional differential equations, sufficient criteria about outer-synchronization of the controlled fractional-order neural networks are derived for structure-dependent centralized data-sampling, state-dependent centralized data-sampling, and state-dependent decentralized data-sampling, respectively. …”
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  8. 728

    Spectral convolutional neural network chip for in-sensor edge computing of incoherent natural light by Kaiyu Cui, Shijie Rao, Sheng Xu, Yidong Huang, Xusheng Cai, Zhilei Huang, Yu Wang, Xue Feng, Fang Liu, Wei Zhang, Yali Li, Shengjin Wang

    Published 2025-01-01
    “…Abstract Optical neural networks are considered next-generation physical implementations of artificial neural networks, but their capabilities are limited by on-chip integration scale and requirement for coherent light sources. …”
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    Robust Asymptotical Stability and Stabilization of Fractional-Order Complex-Valued Neural Networks with Delay by Jingjing Zeng, Xujun Yang, Lu Wang, Xiaofeng Chen

    Published 2021-01-01
    “…The robust asymptotical stability and stabilization for a class of fractional-order complex-valued neural networks (FCNNs) with parametric uncertainties and time delay are considered in this paper. …”
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  13. 733
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    An Evaluation Model for Tailings Storage Facilities Using Improved Neural Networks and Fuzzy Mathematics by Sen Tian, Jianhong Chen

    Published 2014-01-01
    “…This paper establishes a reasonable TSF safety evaluation index system and puts forward a new TSF safety evaluation model by combining the theories for the analytic hierarchy process (AHP) and improved back-propagation (BP) neural network algorithm. The varying proportions of cross validation were calculated, demonstrating that this method has better evaluation performance with higher learning efficiency and faster convergence speed and avoids the oscillation in the training process in traditional BP neural network method and other primary neural network methods. …”
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    Risk Prediction Algorithm of Social Security Fund Operation Based on RBF Neural Network by Linxuan Yang

    Published 2021-01-01
    “…Finally, the RBF neural network is used for comprehensive risk warning. …”
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  19. 739

    Verification of a static (off-line) signature using a convolutional neural network by U. Yu. Akhundjanov, V. V. Starovoitov

    Published 2022-06-01
    “…These images served as the source data for the convolutional neural network.As a result of testing the proposed approach, the average accuracy of the correct classification was achieved on medium-sized images and is equal to 93.33%.…”
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  20. 740

    Energy-efficient analog-domain aggregator circuit for RRAM-based neural network accelerators by Khaled Humood, Yihan Pan, Shiwei Wang, Alexander Serb, Themis Prodromakis

    Published 2025-02-01
    “…Recently, there has been notable progress in the advancement of RRAM-based Compute-In-Memory (CIM) architectures, showing promise in accelerating neural networks with remarkable energy efficiency and parallelism. …”
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