Nonlinear System Identification using Spatio-Temporal RBF-NN
In this submission, I implemented RBF, Fractional RBF, and Spatio-Temporal RBF Neural Network for nonlinear system identification task
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Herein, you will find three variants of radial basis function neural network (RBF-NN) for nonlinear system identification task. In particular, I implemented RBF with conventional and fractional gradient descent, and compared the performance with spatio-temporal RBF-NN.
* For citations see [cite as] section
引用
Shujaat Khan (2026). Nonlinear System Identification using Spatio-Temporal RBF-NN (https://jp.mathworks.com/matlabcentral/fileexchange/68415-nonlinear-system-identification-using-spatio-temporal-rbf-nn), MATLAB Central File Exchange. に取得済み.
Khan, Shujaat, et al. “A Novel Adaptive Kernel for the RBF Neural Networks.” Circuits, Systems, and Signal Processing, vol. 36, no. 4, Springer Nature, July 2016, pp. 1639–53, doi:10.1007/s00034-016-0375-7.
Khan, Shujaat, et al. “A Fractional Gradient Descent-Based RBF Neural Network.” Circuits, Systems, and Signal Processing, vol. 37, no. 12, Springer Nature America, Inc, May 2018, pp. 5311–32, doi:10.1007/s00034-018-0835-3.
Khan, Shujaat, et al. “Spatio-Temporal RBF Neural Networks.” 2018 3rd {IEEE} International Conference on Emerging Trends in Engineering, Sciences and Technology ({ICEEST}), {IEEE}, 2018
謝辞
ヒントを得たファイル: Nonlinear System Identification using RBF Neural Network
