Nonlinear System Identification using Spatio-Temporal RBF-NN

バージョン 1.1.2 (357 KB) 作成者: Shujaat Khan
In this submission, I implemented RBF, Fractional RBF, and Spatio-Temporal RBF Neural Network for nonlinear system identification task
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更新 2018/12/5

ライセンスの表示

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 (2024). Nonlinear System Identification using Spatio-Temporal RBF-NN (https://www.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.

その他のスタイルを見る

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.

その他のスタイルを見る

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

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バージョン 公開済み リリース ノート
1.1.2

- update citation information

1.1.1

- title change

1.1

- Comparison with conventional and fractional variant

1.0.2

- Simplification of code syntax

1.0.1

- Example added

1.0.0