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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:
9783030015190

Forlag:
Springer Nature Switzerland AG

Indbinding:
Hardback

Sideantal:
340

Udgivet:
17. oktober 2018

Udgave:
12019

Vægt:
688 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-2017

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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