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ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments.

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Sprog:
Engelsk

ISBN:
9783030233068

Forlag:
Springer Nature Switzerland AG

Indbinding:
Hardback

Sideantal:
347

Udgivet:
30. juni 2019

Udgave:
12020

Vægt:
699 g.

Leveringstid: 8-11 hverdage.
Forventet levering: 13. december 2024

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Forlænget returret til d. 31. januar 2025

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Beskrivelse af Proceedings of ELM 2018

ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments.

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