Receptive field atlas and related CNN models

V. Gál, J. Hámori, T. Roska, D. Bálya, Z. S. Borostyánkoi, M. Brendel, K. Lotz, L. Négyessy, L. Orzó, I. Petrás, C. S. Rekeczky, J. Takács, P. Venetiáner, Z. Vidnyánszky, Á Zarándy

Research output: Contribution to journalArticle

11 Citations (Scopus)


In this paper we demonstrate the potential of the cellular nonlinear/neural network paradigm (CNN) that of the analogic cellular computer architecture (called CNN Universal Machine -CNN-UM) in modeling different parts and aspects of the nervous system. The structure of the living sensory systems and the CNN share a lot of features in common: local interconnections ("receptive field architecture"), nonlinear and delayed synapses for the processing tasks, the potentiality of feedback and using the advantages of both the analog and logic signal-processing mode. The results of more than ten years of cooperative work of many engineers and neurobiologists have been collected in an atlas: what we present here is a kind of selection from these studies emphasizing the flexibility of the CNN computing: visual, tactile and auditory modalities are concerned.

Original languageEnglish
Pages (from-to)551-584
Number of pages34
JournalInternational Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Issue number2
Publication statusPublished - Feb 2004



  • CNN
  • Cellular neural networks
  • Cellular nonlinear networks
  • Feedback network layers
  • Feedforward
  • Local interconnections
  • Receptive field calculus
  • Receptive fields
  • Visual, auditory and tactile system modeling

ASJC Scopus subject areas

  • Modelling and Simulation
  • Engineering (miscellaneous)
  • General
  • Applied Mathematics

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