Bio-inspired nano-sensor-enhanced CNN visual computer

Wolfgang Porod, Frank Werblin, Leon O. Chua, Tamás Roska, Ángel Rodriguez-Vázquez, Botond Roska, Patrick Fay, Gary H. Bernstein, Yih Fang Huang, Árpád I. Csurgay

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Nanotechnology opens new ways to utilize recent discoveries in biological image processing by translating the underlying functional concepts into the design of CNN (cellular neural/nonlinear network)-based systems incorporating nanoelectronic devices. There is a natural intersection joining studies of retinal processing, spatio-temporal nonlinear dynamics embodied in CNN, and the possibility of miniaturizing the technology through nanotechnology. This intersection serves as the spring-board for our multidisciplinary project. Biological feature and motion detectors map directly into the spatio-temporal dynamics of CNN for target recognition, image stabilization, and tracking. The neural interactions underlying color processing will drive the development of nanoscale multispectral sensor arrays for image fusion. Implementing such nanoscale sensors on a CNN platform will allow the implementation of device feedback control, a hallmark of biological sensory systems. These biologically inspired CNN subroutines are incorporated into the new world of analog-and-logic algorithms and software, containing also many other active-wave computing mechanisms, including nature-inspired (physics and chemistry) as well as PDE-based sophisticated spatio-temporal algorithms. Our goal is to design and develop several miniature prototype devices for target detection, navigation, tracking, and robotics. This paper presents an example illustrating the synergies emerging from the convergence of nanotechnology, biotechnology, and information and cognitive science.

Original languageEnglish
Pages (from-to)92-109
Number of pages18
JournalAnnals of the New York Academy of Sciences
Volume1013
DOIs
Publication statusPublished - Jan 1 2004

Keywords

  • Analog-and-logical visual computing
  • Cellular neural/nonlinear network (CNN)
  • Feature and motion detection
  • Nanoscale optical/infrared sensor
  • Retinal information processing
  • Target recognition and tracking
  • Wave computing

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • History and Philosophy of Science

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  • Cite this

    Porod, W., Werblin, F., Chua, L. O., Roska, T., Rodriguez-Vázquez, Á., Roska, B., Fay, P., Bernstein, G. H., Huang, Y. F., & Csurgay, Á. I. (2004). Bio-inspired nano-sensor-enhanced CNN visual computer. Annals of the New York Academy of Sciences, 1013, 92-109. https://doi.org/10.1196/annals.1305.011