Stochastic bitstream-based CNN and its implementation on FPGA

  • Authors:

  • Ádám Rák;Balázs Gergely Soós;György Cserey

  • Affiliations:

  • Faculty of Information Technology, Pázmány Péter Catholic University, Práter u. 50-a, Budapest 1083, Hungary;Faculty of Information Technology, Pázmány Péter Catholic University, Práter u. 50-a, Budapest 1083, Hungary;Fac. of Info. Technol., Pázmány Péter Catholic Univ., Práter u. 50-a, Budapest and Infobionic and Neurobiological Plasticity Res. Grp., Hungarian Acad. of Sci., Semmelweis Univ ...

  • Venue:
  • International Journal of Circuit Theory and Applications - CNNA part II
  • Year:
  • 2009

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Abstract

In this paper, we present a new type of cellular nonlinear network (CNN) model and FPGA implementation of cellular nonlinear network universal machine. Our approach uses stochastic bitstreams as data carriers. With the help of stochastic data streams more complex nonlinear cell interactions can be realized than conventional CNN hardware implementations have. The accuracy as indexed by bit depth resolution can be improved at the expense of computation time without influencing hardware complexity. Our simulation results prove the universality and utility of the model. Our experimental results show that the proposed model can be implemented on an FPGA hardware. Copyright © 2008 John Wiley & Sons, Ltd.