Chaotic Time Series Prediction using Spatio-Temporal RBF-NN

버전 1.0.1 (1.27 MB) 작성자: Shujaat Khan

Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks

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업데이트 날짜: 2018/12/5

라이선스 보기

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

인용 양식

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. 검색됨 2024/4/26.

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.

양식 더 보기

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.

양식 더 보기

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

MATLAB 릴리스 호환 정보

개발 환경: R2018b

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받음: Mackey-Glass time series generator

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Time_Series_Prediction

버전	게시됨	릴리스 정보
1.0.1	2018/12/5	-update citation information	다운로드
1.0.0	2018/11/26		다운로드

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} }