Chaotic Time Series Prediction using Spatio-Temporal RBF-NN

Version 1.0.1 (1,27 MB) von Shujaat Khan

Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks

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Herein, you will find two variants of radial basis function neural network (RBF-NN) for chaotic time series prediction task. In particular, I implemented RBF with conventional and compared the performance with spatio-temporal RBF-NN for Mackey-Glass time series prediction.

* For citations see [cite as] section

Zitieren als

Shujaat Khan (2024). Chaotic Time Series Prediction using Spatio-Temporal RBF-NN (https://www.mathworks.com/matlabcentral/fileexchange/69523-chaotic-time-series-prediction-using-spatio-temporal-rbf-nn), MATLAB Central File Exchange. Abgerufen 26. Juli 2024.

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.

Mehrere Stile anzeigen

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.

Mehrere Stile anzeigen

Sadiq, Alishba, et al. “Chaotic Time Series Prediction using 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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Inspiriert von: Mackey-Glass time series generator

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Time_Series_Prediction

Version	Veröffentlicht	Versionshinweise
1.0.1	5. Dez 2018	-update citation information	Herunterladen
1.0.0	26. Nov 2018		Herunterladen

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} }

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} }