Hopfield-Tank neural net: Walsh to Fourier transform

D. A. Karras, S. J. Varoufakis, G. E. Antoniou, G. B. Carayannis

Research output: Contribution to journalArticlepeer-review


A simple method for the computation of the Discrete Fourier Transform (DFT) from the Walsh Transform, using the Neural Network model of Hopfield and Tank, is presented. The proposed method circumvents the algorithmic complexity of the DFT. The computation time for the evaluation of the DFT coefficients depends upon a time constant which characterizes the neural network.

Original languageEnglish
Pages (from-to)37-41
Number of pages5
Issue number1-2
StatePublished - Feb 1992

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence


  • Fourier transform
  • Hopfield-Tank model
  • Neural networks
  • Walsh transform


Dive into the research topics of 'Hopfield-Tank neural net: Walsh to Fourier transform'. Together they form a unique fingerprint.

Cite this