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ELM in nonstationary environment
Extreme Learning Machine and its variants for Time-Varying Neural Networks case study
Yibin Ye, Stefano Squartini, Francesco Piazza
Livre broché | Anglais
65,45 €
+ 130 points
Description
System identification in nonstationary environment represents a challenging problem and an advaned neural architecture namely Time-Varying Neural Net- works (TV-NN) has shown remarkable identification properties in nonlinear and nonstationary conditions. Time-varying weights, each being a linear com- bination of a certain set of basis functions, are used in such kind of networks instead of stable ones, which inevitalbly increases the number of free parame- ters. Therefore, an Extreme Learning Machine (ELM) approach is developed to accelerate the training procedure for TV-NN. What is more, in order to ob- tain a more compact structure, or determine several important parameters, or update the network more efficiently in online case, several variants of ELM-TV are proposed and discussed in the book. Related computer simulations have been carried out and show the effectiveness of the algorithms.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 88
- Langue:
- Anglais
Caractéristiques
- EAN:
- 9783659248900
- Date de parution :
- 09-11-12
- Format:
- Livre broché
- Dimensions :
- 150 mm x 220 mm
- Poids :
- 150 g
Seulement chez Librairie Club
+ 130 points sur votre carte client de Librairie Club
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