Reservoir Computing Approach to Robust Computation Using Unreliable Nanoscale Networks

  • Alireza Goudarzi
  • Matthew R. Lakin
  • Darko Stefanovic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8553)


As we approach the physical limits of CMOS technology, advances in materials science and nanotechnology are making available a variety of unconventional computing substrates that can potentially replace top-down-designed silicon-based computing devices. Inherent stochasticity in the fabrication process and nanometer scale of these substrates inevitably lead to design variations, defects, faults, and noise in the resulting devices. A key challenge is how to harness such devices to perform robust computation. We propose reservoir computing as a solution. In reservoir computing, computation takes place by translating the dynamics of an excited medium, called a reservoir, into a desired output. This approach eliminates the need for external control and redundancy, and the programming is done using a closed-form regression problem on the output, which also allows concurrent programming using a single device. Using a theoretical model, we show that both regular and irregular reservoirs are intrinsically robust to structural noise as they perform computation.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Alireza Goudarzi
    • 1
  • Matthew R. Lakin
    • 1
  • Darko Stefanovic
    • 1
    • 2
  1. 1.Department of Computer ScienceUniversity of New MexicoAlbuquerqueUSA
  2. 2.Center for Biomedical EngineeringUniversity of New MexicoAlbuquerqueUSA

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