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

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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. 取得日: 2026/1/23.

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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作成: R2015a

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ヒントを得たファイル: Nonlinear System Identification using RBF Neural Network

Nonlinear_System_Identification

バージョン	公開済み	リリースノート
1.1.2	2018/12/5	- update citation information	ダウンロード
1.1.1	2018/11/26	- title change	ダウンロード
1.1	2018/11/26	- Comparison with conventional and fractional variant	ダウンロード
1.0.2	2018/8/15	- Simplification of code syntax	ダウンロード
1.0.1	2018/8/6	- Example added	ダウンロード
1.0.0	2018/8/6		ダウンロード

MLA	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.
APA	Khan, S., Naseem, I., Togneri, R., & Bennamoun, M. (2016). A Novel Adaptive Kernel for the RBF Neural Networks. Circuits, Systems, and Signal Processing, 36(4), 1639–1653. Springer Nature. Retrieved from https://doi.org/10.1007%2Fs00034-016-0375-7
BibTeX	@article{Khan_2016, doi = {10.1007/s00034-016-0375-7}, url = {https://doi.org/10.1007%2Fs00034-016-0375-7}, year = 2016, month = {jul}, publisher = {Springer Nature}, volume = {36}, number = {4}, pages = {1639--1653}, author = {Shujaat Khan and Imran Naseem and Roberto Togneri and Mohammed Bennamoun}, title = {A Novel Adaptive Kernel for the {RBF} Neural Networks}, journal = {Circuits, Systems, and Signal Processing} }

MLA	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.
APA	Khan, S., Naseem, I., Malik, M. A., Togneri, R., & Bennamoun, M. (2018). A Fractional Gradient Descent-Based RBF Neural Network. Circuits, Systems, and Signal Processing, 37(12), 5311–5332. Springer Nature America, Inc. Retrieved from https://doi.org/10.1007%2Fs00034-018-0835-3
BibTeX	@article{Khan_2018, doi = {10.1007/s00034-018-0835-3}, url = {https://doi.org/10.1007%2Fs00034-018-0835-3}, year = 2018, month = {may}, publisher = {Springer Nature America, Inc}, volume = {37}, number = {12}, pages = {5311--5332}, author = {Shujaat Khan and Imran Naseem and Muhammad Ammar Malik and Roberto Togneri and Mohammed Bennamoun}, title = {A Fractional Gradient Descent-Based {RBF} Neural Network}, journal = {Circuits, Systems, and Signal Processing} }

Nonlinear System Identification using Spatio-Temporal RBF-NN

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Nonlinear System Identification using Spatio-Temporal RBF-NN

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Nonlinear_System_Identification

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