Titlebook: Artificial Neural Networks - ICANN 2007; 17th International C Joaquim Marques Sá,Luís A. Alexandre,Danilo Mandic Conference proceedings 200

Watemelon

https://doi.org/10.1007/978-3-540-74690-4Boolean function; algorithmic learning; algorithms; bioinspired computing; biomedical data analysis; clas

FLIT

978-3-540-74689-8Springer-Verlag Berlin Heidelberg 2007

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liposuction

Gang der Versuchsdurchrechnungen,al to achieve their greater prediction ability. A standard training of these neural networks uses pseudoinverse matrix for one-step learning of weights from hidden to output neurons. This regular adaptation of Echo State neural networks was optimized by updating the weights of the dynamic reservoir

悲觀

釘牢

生命層

教義

scrutiny

Versuche mit gasreichen Kohlen,ds on the size of neural networks that are unrealistic to implement. This work provides a computational study for estimating the size of neural networks using as an estimation parameter the size of available training data. We will also show that the size of a neural network is problem dependent and