Global sensitivity analysis approach for input selection and system identification purposes--a new framework for feedforward neural networks.

Fock E

Open source

DOI
10.1109/tnnls.2013.2294437
Published
2014 Aug
Container
IEEE transactions on neural networks and learning systems
Publisher
Not recorded
Open access
no

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BibTeX

@article{allodium:10.1109/tnnls.2013.2294437,
  title = {Global sensitivity analysis approach for input selection and system identification purposes--a new framework for feedforward neural networks.},
  author = {Fock E},
  year = {2014},
  journal = {IEEE transactions on neural networks and learning systems},
  doi = {10.1109/tnnls.2013.2294437},
  url = {https://doi.org/10.1109/tnnls.2013.2294437}
}

RIS

TY  - JOUR
TI  - Global sensitivity analysis approach for input selection and system identification purposes--a new framework for feedforward neural networks.
AU  - Fock E
PY  - 2014
JO  - IEEE transactions on neural networks and learning systems
DO  - 10.1109/tnnls.2013.2294437
UR  - https://doi.org/10.1109/tnnls.2013.2294437
ER  -

APA

E, F. (2014). Global sensitivity analysis approach for input selection and system identification purposes--a new framework for feedforward neural networks.. IEEE transactions on neural networks and learning systems. https://doi.org/10.1109/tnnls.2013.2294437

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