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  4. Reservoir Optimization in Recurrent Neural Networks using Kronecker Kernels
 
conference paper

Reservoir Optimization in Recurrent Neural Networks using Kronecker Kernels

Ajdari Rad, Ali  
•
Jalili, Mahdi  
•
Hasler, Martin  
2008
IEEE ISCAS 2008
IEEE ISCAS 2008

In this paper, using the mathematical properties of self-kronecker-production of small size random matrices, a simple but effective method is presented to optimize the reservoir of an echo state network given a certain task. The experimental results investigating the NARMA system show that few steps of the proposed optimization process can lead to a near optimum solution.

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Type
conference paper
DOI
10.1109/ISCAS.2008.4541556
Web of Science ID

WOS:000258532100221

Author(s)
Ajdari Rad, Ali  
Jalili, Mahdi  
Hasler, Martin  
Date Issued

2008

Publisher

IEEE

Published in
IEEE ISCAS 2008
Start page

868

End page

871

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LANOS  
Event nameEvent placeEvent date
IEEE ISCAS 2008

Seattle, WA

May 18-21, 2008

Available on Infoscience
June 16, 2008
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/26282
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