<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

Determining the Weights of A Fourier Series Neural Network on the Basis of the Multidimensional Discrete Fourier Transform

Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wroclaw, Poland

International Journal of Applied Mathematics and Computer Science

This paper presents a method for training a Fourier series neural network on the basis of the multidimensional discrete Fourier transform. The proposed method...

Determining the Weights of A Fourier Series Neural Network on the Basis of the Multidimensional Discrete Fourier Transform

Publié en ligne: 06 oct. 2008

Pages: 369 - 375

DOI: https://doi.org/10.2478/v10006-008-0033-8

Mots clés
orthogonal neural networks, Fourier series, fast Fourier transform, approximation, nonlinear systems

This content is open access.

Determining the Weights of A Fourier Series Neural Network on the Basis of the Multidimensional Discrete Fourier Transform

Publié en ligne: 06 oct. 2008

Pages: 369 - 375

DOI: https://doi.org/10.2478/v10006-008-0033-8

Mots clésorthogonal neural networks, Fourier series, fast Fourier transform, approximation, nonlinear systems

This content is open access.

Mots clés
orthogonal neural networks, Fourier series, fast Fourier transform, approximation, nonlinear systems