Non-Linear System Identification using recurrent neural network trained with Backpropagation Through Time (BPTT)
Cite As
Shujaat Khan (2021). System Identification using RNN-Backpropagation Through Time (https://www.mathworks.com/matlabcentral/fileexchange/72377-system-identification-using-rnn-backpropagation-through-time), MATLAB Central File Exchange.
Retrieved .
Khan, Shujaat, et al. “A Novel Fractional Gradient-Based Learning Algorithm for Recurrent Neural Networks.” Circuits, Systems, and Signal Processing, vol. 37, no. 2, Springer Nature, May 2017, pp. 593–612, doi:10.1007/s00034-017-0572-z.
Khan, Shujaat, et al. “A Novel Fractional Gradient-Based Learning Algorithm for Recurrent Neural Networks.” Circuits, Systems, and Signal Processing, vol. 37, no. 2, Springer Nature, May 2017, pp. 593–612, doi:10.1007/s00034-017-0572-z.
APA
Khan, S., Ahmad, J., Naseem, I., & Moinuddin, M. (2017). A Novel Fractional Gradient-Based Learning Algorithm for Recurrent Neural Networks. Circuits, Systems, and Signal Processing, 37(2), 593–612. Springer Nature. Retrieved from https://doi.org/10.1007%2Fs00034-017-0572-z
BibTeX
@article{Khan_2017,
doi = {10.1007/s00034-017-0572-z},
url = {https://doi.org/10.1007%2Fs00034-017-0572-z},
year = 2017,
month = {may},
publisher = {Springer Nature},
volume = {37},
number = {2},
pages = {593--612},
author = {Shujaat Khan and Jawwad Ahmad and Imran Naseem and Muhammad Moinuddin},
title = {A Novel Fractional Gradient-Based Learning Algorithm for Recurrent Neural Networks},
journal = {Circuits, Systems, and Signal Processing}
}
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