Analogic cellular PDE machines

Csaba Rekeczky, István Szatmári, Péter Földesy, Tamás Roska

Research output: Contribution to conferencePaper

4 Citations (Scopus)


This paper gives an overview on analogic cellular array architectures that can also be used to approximate partial differential equations (PDEs). Cellular arrays are massively parallel computing structures composed of cells placed on a regular grid. These cells interact locally and the array can have both local and global dynamics. The software of this architecture is an analogic algorithm that builds on analog and logical spatio-temporal instructions of the underlying hardware, that is a locally connected cellular nonlinear network (CNN, [1]-[5]). Within this framework two classes of PDEs, motivated also by image processing methodologies will be discussed: (i) reaction-diffusion (local) types and (ii) contrast modification (global) types. It will be shown that based on cellular diffusion and wave-computing formulations these classes can be approximated on existing CNN Universal Machine (CNN-UM), [4]) chips (e.g. [8]). Thus, the last generation of stored program topographic array microprocessors with integrated sensing and computing could also be viewed as the first prototypes of analogic cellular PDE MACHINEs implemented on silicon.

Original languageEnglish
Number of pages6
Publication statusPublished - Jan 1 2002
Event2002 International Joint Conference on Neural Networks (IJCNN'02) - Honolulu, HI, United States
Duration: May 12 2002May 17 2002


Other2002 International Joint Conference on Neural Networks (IJCNN'02)
CountryUnited States
CityHonolulu, HI


ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Rekeczky, C., Szatmári, I., Földesy, P., & Roska, T. (2002). Analogic cellular PDE machines. 2033-2038. Paper presented at 2002 International Joint Conference on Neural Networks (IJCNN'02), Honolulu, HI, United States.