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  • Hybrid Learning Algorithm o... Hybrid Learning Algorithm of Radial Basis Function Networks for Reliability Analysis
    Zhang, Dequan; Zhang, Ning; Ye, Nan ... IEEE transactions on reliability, 2021-Sept., 2021-9-00, 20210901, Volume: 70, Issue: 3
    Journal Article
    Peer reviewed

    With the wide application of industrial robots in the field of precision machining, reliability analysis of positioning accuracy becomes increasingly important for industrial robots. Since the ...
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  • Observer-Based Adaptive Sli... Observer-Based Adaptive Sliding Mode Control of NPC Converters: An RBF Neural Network Approach
    Yunfei Yin; Jianxing Liu; Sanchez, Juan Antonio ... IEEE transactions on power electronics, 04/2019, Volume: 34, Issue: 4
    Journal Article
    Peer reviewed

    This paper proposes a novel control strategy for three-level neutral-point-clamped (NPC) power converter. The proposed control scheme consists of three control loops, i.e., instantaneous power ...
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  • Advantages of Radial Basis ... Advantages of Radial Basis Function Networks for Dynamic System Design
    Hao Yu; Tiantian Xie; Paszczynski, S. ... IEEE transactions on industrial electronics (1982), 2011-Dec., 2011-12-00, 20111201, Volume: 58, Issue: 12
    Journal Article
    Peer reviewed

    Radial basis function (RBF) networks have advantages of easy design, good generalization, strong tolerance to input noise, and online learning ability. The properties of RBF networks make it very ...
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  • Hierarchical Estimation App... Hierarchical Estimation Approach for RBF-AR Models With Regression Weights Based on the Increasing Data Length
    Zhou, Yihong; Zhang, Xiao; Ding, Feng IEEE transactions on circuits and systems. II, Express briefs, 12/2021, Volume: 68, Issue: 12
    Journal Article
    Peer reviewed

    In the radial basis function-based state-dependent autoregressive (RBF-AR) models with regression weights, the local linear models are included between the hidden layers and the output layers of the ...
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  • A Novel RBF Training Algori... A Novel RBF Training Algorithm for Short-Term Electric Load Forecasting and Comparative Studies
    Cecati, Carlo; Kolbusz, Janusz; Rozycki, Pawel ... IEEE transactions on industrial electronics (1982), 10/2015, Volume: 62, Issue: 10
    Journal Article
    Peer reviewed

    Because of their excellent scheduling capabilities, artificial neural networks (ANNs) are becoming popular in short-term electric power system forecasting, which is essential for ensuring both ...
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  • Event-Based Finite-Time Neu... Event-Based Finite-Time Neural Control for Human-in-the-Loop UAV Attitude Systems
    Lin, Guohuai; Li, Hongyi; Ahn, Choon Ki ... IEEE transaction on neural networks and learning systems, 12/2023, Volume: 34, Issue: 12
    Journal Article

    This article focuses on the event-based finite-time neural attitude consensus control problem for the six-rotor unmanned aerial vehicle (UAV) systems with unknown disturbances. It is assumed that the ...
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  • An Incremental Design of Ra... An Incremental Design of Radial Basis Function Networks
    Hao Yu; Reiner, Philip D.; Tiantian Xie ... IEEE transaction on neural networks and learning systems, 10/2014, Volume: 25, Issue: 10
    Journal Article

    This paper proposes an offline algorithm for incrementally constructing and training radial basis function (RBF) networks. In each iteration of the error correction (ErrCor) algorithm, one RBF unit ...
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  • Soft Computing-Based EEG Cl... Soft Computing-Based EEG Classification by Optimal Feature Selection and Neural Networks
    Bhatti, Muhammad Hamza; Khan, Javeria; Khan, Muhammad Usman Ghani ... IEEE transactions on industrial informatics, 10/2019, Volume: 15, Issue: 10
    Journal Article

    Brain computer interface translates electroencephalogram (EEG) signals into control commands so that paralyzed people can control assistive devices. This human thought translation is a very ...
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  • Battery Aging Assessment fo... Battery Aging Assessment for Real-World Electric Buses Based on Incremental Capacity Analysis and Radial Basis Function Neural Network
    She, Chengqi; Wang, Zhenpo; Sun, Fengchun ... IEEE transactions on industrial informatics, 05/2020, Volume: 16, Issue: 5
    Journal Article

    Accurate battery aging prediction is essential for ensuring efficient, reliable, and safe operation of battery systems in electric vehicle application. This article presents a novel battery aging ...
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  • Fast Adaptive Gradient RBF ... Fast Adaptive Gradient RBF Networks For Online Learning of Nonstationary Time Series
    Liu, Tong; Chen, Sheng; Liang, Shan ... IEEE transactions on signal processing, 2020, Volume: 68
    Journal Article
    Peer reviewed
    Open access

    For a learning model to be effective in online modeling of nonstationary data, it must not only be equipped with high adaptability to track the changing data dynamics but also maintain low complexity ...
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