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Model Complexity of Neural Networks - a Seeming Paradox
The paper investigates limitations of one-hidden-layer artificial neural networks for solving high-dimensional tasks.
IN - Informatika
- 2015 •
- D •
- Link
Rok uplatnění
D - Stať ve sborníku
Výsledek na webu
Approximating Multivariable Functions by Feedforward Neural Nets
Theoretical results on approximation of multivariable functions by feedforward neural networks are surveyed. Some proofs of universal approximation capabilities of rates of decrease of approximation errors with increasing <...
IN - Informatika
- 2013 •
- C •
- Link
Rok uplatnění
C - Kapitola v odborné knize
Výsledek na webu
Accuracy of surrogate solutions of integral equations by feedforward networks
Surrogate solutions of Fredholm integral equations by feedforward neural networks are investigated theoretically. Convergence of surrogate solutions computable by networks with increasing numbers of computational u...
IN - Informatika
- 2014 •
- C •
- Link
Rok uplatnění
C - Kapitola v odborné knize
Výsledek na webu
Implementation of Kolmogorov Learning Algorithm for Feedforward Neural Networks.
We present a learning algorithm for feedforward neural networks that is based on Kolmogorov theorem concerning composition of n-dimensional countinuous function from one-dimensional continuous functions. A through analysis ...
BA - Obecná matematika
- 2001 •
- D
Rok uplatnění
D - Stať ve sborníku
The Application of Structured Feedforward Neural Networks to the Modelling of the Daily Series of Currency in Circulation
The paper introduces feedforward structured neural network model and discusses its applicability to the forecasting of the currency in circulation. The forecasting performance of the new neural network...
BA - Obecná matematika
- 2005 •
- D
Rok uplatnění
D - Stať ve sborníku
Surrogate solutions of Fredholm equations by feedforward networks
Surrogate solutions of Fredholm integral equations by feedforward neural networks are investigated theoretically. Convergence of surrogate solutions computable by networks with increasing numbers of computational u...
IN - Informatika
- 2012 •
- D
Rok uplatnění
D - Stať ve sborníku
NONLINEAR MODELING OF LABORATORY MODEL AMIRA DR300 BY FEEDFORWARD NEURAL NETWORK
Purpose of this paper is to design a nonlinear feedforward neural network model of a laboratory model AMIRA DR300 (made by AMIRA, Duisburg, Germany). This device consists position sensor. The first engine ...
BC - Teorie a systémy řízení
- 2011 •
- D
Rok uplatnění
D - Stať ve sborníku
Universality and Complexity of Approximation of Multivariable Functions by Feedforward Networks.
A theoretical framework for investigation of approximation capabilities of feed-forward networks is presented in the context of nonlinear approximation theory. Some recent results of universal approximation property and estimates of netw...
BA - Obecná matematika
- 2002 •
- D
Rok uplatnění
D - Stať ve sborníku
Kolmogorov Learning for Feedforward Networks.
We present a learning algorithm for feedforward neural networks that is based on Kolmogorov theorem concerning composition of n-dimensional continuous function from one-dimensional continuous functions. A thorough analysis ...
BA - Obecná matematika
- 2001 •
- D
Rok uplatnění
D - Stať ve sborníku
An orthogonal neural network for nonlinear function modelling
The paper is dealing with the multilayer feedforward network...
JC - Počítačový hardware a software
- 2007 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
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