Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications

0485562 - ÚI 2021 RIV CH eng M - Monography Chapter
Kůrková, Věra - Kainen, P.C.
Integral Transforms Induced by Heaviside Perceptrons.
Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications. Cham: Springer, 2020 - (Kosheleva, O.; Shary, S.; Xiang, G.; Zapatrin, R.), s. 631-649. Studies in Computational Intelligence, 835. ISBN 978-3-030-31040-0
R&D Projects: GA ČR GA15-18108S; GA ČR(CZ) GA18-23827S
Institutional support: RVO:67985807
Keywords : representations of functions by neural networks * Haeviside perceptrons * integral transforms
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

We investigate an integral transform with kernel induced by perceptrons with the Heaviside activation function. Representation theorems are given expressing sufficiently smooth functions as “infinite Heaviside perceptron networks”. The representation is exploited to obtain estimates of rates of approximation of these functions by networks with increasing numbers of units.
Permanent Link: http://hdl.handle.net/11104/0280525