Ghent University Academic Bibliography

Advanced

Pattern classification with CNNs as reservoirs

David Verstraeten UGent, Samuel Xavier-de-Souza, Benjamin Schrauwen, Johan Suykens, Dirk Stroobandt UGent and Joos Vandewalle (2008) Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA).
abstract
Reservoir Computing is a novel method in the field of neural networks and machine learning, which combines the computational power of a nonlinear dynamic system with the ease of training of a linear classifier. The basic setup is as follows: a sufficiently complex network of nonlinear nodes (called the reservoir) is excited by an input signal, and the instantaneous dynamic response of the system is then used to train a simple linear readout function.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
Cellular Neural Networks, Reservoir Computing
in
Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA)
pages
4 pages
conference name
International Symposium on Nonlinear Theory and its Applications (NOLTA)
conference location
Budapest, Hungary
conference start
2008-09-07
conference end
2008-09-10
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
678913
handle
http://hdl.handle.net/1854/LU-678913
date created
2009-06-05 09:09:42
date last changed
2016-12-19 15:36:15
@inproceedings{678913,
  abstract     = {Reservoir Computing is a novel method in the field of neural networks and machine learning, which combines the computational power of a nonlinear dynamic system with the ease of training of a linear classifier. The basic setup is as follows: a sufficiently complex network of nonlinear nodes (called the reservoir) is excited by an input signal, and the instantaneous dynamic response of the system is then used to train a simple linear readout function.},
  author       = {Verstraeten, David and Xavier-de-Souza, Samuel and Schrauwen, Benjamin and Suykens, Johan and Stroobandt, Dirk and Vandewalle, Joos},
  booktitle    = {Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA)},
  keyword      = {Cellular Neural Networks,Reservoir Computing},
  language     = {eng},
  location     = {Budapest, Hungary},
  pages        = {4},
  title        = {Pattern classification with CNNs as reservoirs},
  year         = {2008},
}

Chicago
Verstraeten, David, Samuel Xavier-de-Souza, Benjamin Schrauwen, Johan Suykens, Dirk Stroobandt, and Joos Vandewalle. 2008. “Pattern Classification with CNNs as Reservoirs.” In Proceedings of the International Symposium on Nonlinear Theory and Its Applications (NOLTA).
APA
Verstraeten, D., Xavier-de-Souza, S., Schrauwen, B., Suykens, J., Stroobandt, D., & Vandewalle, J. (2008). Pattern classification with CNNs as reservoirs. Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA). Presented at the International Symposium on Nonlinear Theory and its Applications (NOLTA).
Vancouver
1.
Verstraeten D, Xavier-de-Souza S, Schrauwen B, Suykens J, Stroobandt D, Vandewalle J. Pattern classification with CNNs as reservoirs. Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA). 2008.
MLA
Verstraeten, David, Samuel Xavier-de-Souza, Benjamin Schrauwen, et al. “Pattern Classification with CNNs as Reservoirs.” Proceedings of the International Symposium on Nonlinear Theory and Its Applications (NOLTA). 2008. Print.