On Kolmogorov's Superposition Theorem and its Applications
A Nonlinear Model for Numerical Function Reconstruction from Discrete Data Sets in Higher Dimensions
Auteurs
Boekbeoordeling
Meer over het boek
The book introduces a Regularization Network approach utilizing Kolmogorov's superposition theorem to reconstruct higher-dimensional continuous functions from discrete data points. It presents a new constructive proof of the theorem and explores its various versions, linking them to well-known approximation methods and Neural Networks. The work addresses the challenge of the curse of dimensionality, proposing a nonlinear model for function reconstruction within a reproducing kernel Hilbert space. It includes verification and analysis through numerous numerical examples.
Een boek kopen
On Kolmogorov's Superposition Theorem and its Applications, Jürgen Braun
- Taal
- Jaar van publicatie
- 2010
- product-detail.submit-box.info.binding
- (Paperback)
Betaalmethoden
We missen je recensie hier.
- Titel
- On Kolmogorov's Superposition Theorem and its Applications
- Ondertitel
- A Nonlinear Model for Numerical Function Reconstruction from Discrete Data Sets in Higher Dimensions
- Taal
- Engels
- Auteurs
- Jürgen Braun
- Jaar van publicatie
- 2010
- Formaat
- Paperback
- Aantal pagina's
- 192
- ISBN13
- 9783838116372
- Reeks
- Tags
- Natuur
- Beoordeling
- 3 van 5
- Aantekening
- The book introduces a Regularization Network approach utilizing Kolmogorov's superposition theorem to reconstruct higher-dimensional continuous functions from discrete data points. It presents a new constructive proof of the theorem and explores its various versions, linking them to well-known approximation methods and Neural Networks. The work addresses the challenge of the curse of dimensionality, proposing a nonlinear model for function reconstruction within a reproducing kernel Hilbert space. It includes verification and analysis through numerous numerical examples.