Construction and approximation for a class of feedforward neural networks with sigmoidal function
From MaRDI portal
Publication:6052306
DOI10.1142/s0219691323500285MaRDI QIDQ6052306
Hailiang Ye, Xin-Hong Meng, Feilong Cao, Jinyao Yan
Publication date: 21 September 2023
Published in: International Journal of Wavelets, Multiresolution and Information Processing (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The errors of simultaneous approximation of multivariate functions by neural networks
- The ridge function representation of polynomials and an application to neural networks
- The approximation operators with sigmoidal functions
- Uniform approximation by neural networks
- Rate of convergence of some neural network operators to the unit-univariate case
- Multilayer feedforward networks are universal approximators
- The rate of approximation of Gaussian radial basis neural networks in continuous function space
- Approximation rates for neural networks with encodable weights in smoothness spaces
- On a problem of Hornik
- Pointwise and uniform approximation by multivariate neural network operators of the max-product type
- Simultaneous \(\mathbf L^p\)-approximation order for neural networks
- Mathematical Models in Population Biology and Epidemiology
- Universal approximation bounds for superpositions of a sigmoidal function
- Mathematical modeling in economics, ecology and the environment
- Approximation by superpositions of a sigmoidal function
This page was built for publication: Construction and approximation for a class of feedforward neural networks with sigmoidal function