On Kolmogorov's Superposition Theorem and its Applications
A Nonlinear Model for Numerical Function Reconstruction from Discrete Data Sets in Higher Dimensions
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Hodnocení knihy
Více o knize
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.
Nákup knihy
On Kolmogorov's Superposition Theorem and its Applications, Jürgen Braun
- Jazyk
- Rok vydání
- 2010
- Vazba
- (měkká)
Doručení
Platební metody
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- Titul
- On Kolmogorov's Superposition Theorem and its Applications
- Podtitul
- A Nonlinear Model for Numerical Function Reconstruction from Discrete Data Sets in Higher Dimensions
- Jazyk
- anglicky
- Autoři
- Jürgen Braun
- Rok vydání
- 2010
- Vazba
- měkká
- Počet stran
- 192
- ISBN13
- 9783838116372
- Série
- Štítky
- Naučná literatura, Učebnice, Věda & Matematika, Příroda, Vysokoškolské učebnice, Věda, Matematika, Matematika a logika
- Hodnocení
- 3 z 5
- Anotace
- 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.