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Universal Approximation Theorem for Vector- and Hypercomplex-Valued Neural Networks

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Valle, Marcos Eduardo, Vital, Wington L., Vieira, Guilherme
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Neural and Evolutionary Computing
Accesso online:	Acceder al recurso
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