Computational frameworks for the fast Fourier transform
Computational frameworks for the fast Fourier transform
Fast Fourier transforms for nonequispaced data
SIAM Journal on Scientific Computing
On function recovery by neural networks based on orthogonal expansions
Proceedings of the second world congress on Nonlinear analysts: part 3
Learning and Design of Principal Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Independent component analysis: algorithms and applications
Neural Networks
Digital Image Processing
International Journal of Intelligent Systems
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This paper presents a method for training a Fourier series neural network on the basis of the multidimensional discrete Fourier transform. The proposed method is characterized by low computational complexity. The article shows how the method can be used for modelling dynamic systems.