Measure Theoretic Results for Approximation by Neural Networks with Limited Weights
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor and Francis Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this article, we study approximation properties of single hidden layer neural networks with weights varying in finitely many directions and with thresholds from an open interval. We obtain a necessary and simultaneously su?cient measure theoretic condition for density of such networks in the space of continuous functions. Further, we prove a density result for neural networks with a specifically constructed activation function and a fixed number of neurons. © 2017 Taylor & Francis.
Açıklama
Anahtar Kelimeler
Activation function, Borel measure, density, lightning bolt, neural network, orbit, orthogonal measure, weak convergence
Kaynak
Numerical Functional Analysis and Optimization
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
38
Sayı
7
