Order estimation in affine state-space neural networks

The problem of order evaluation for an affine state-space neural network or equivalently the estimation of the number of neurons to be inserted in the hidden layer in a recurrent neural network is here addressed. The proposed method is based on a singular value decomposition applied to an oblique su...

Full description

Saved in:
Bibliographic Details
Published inProceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05 pp. 132 - 137
Main Authors Gil, P., Henriques, J., Dourado, A., Duarte-Ramos, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Artificial neural networks
Gas insulated transmission lines
Informatics
Intelligent networks
Network topology
Neural networks
Neurons
Nonlinear dynamical systems
Recurrent neural networks
State estimation
Online AccessGet full text

Cover

More Information
Summary:The problem of order evaluation for an affine state-space neural network or equivalently the estimation of the number of neurons to be inserted in the hidden layer in a recurrent neural network is here addressed. The proposed method is based on a singular value decomposition applied to an oblique subspace projection given as the projection of the row space of future outputs into the past inputs-outputs row space, along the future inputs row space.
ISBN:9780780389427
0780389425
DOI:10.1109/SMCIA.2005.1466961