On the Kolmogorov neural networks
Publication date
2024-08
Authors
Ismayilova, Aysu
Ismailov, Vugar E.
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Document Type
Article
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taverne
Abstract
In this paper, we show that the Kolmogorov two hidden layer neural network model with a continuous, discontinuous bounded and unbounded activation function in the second hidden layer can precisely represent continuous, discontinuous bounded and all unbounded multivariate functions, respectively.
Keywords
Conjugate operator, Dual space, Indicator function, Kolmogorov's superposition theorem, Linear functional, Lipschitz function, Taverne, Cognitive Neuroscience, Artificial Intelligence
Citation
Ismayilova, A & Ismailov, V E 2024, 'On the Kolmogorov neural networks', Neural Networks, vol. 176, 106333, pp. 1-6. https://doi.org/10.1016/j.neunet.2024.106333