Blar i TKD - Institutt for informasjonsteknologi på emneord "Cellular automata"

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    • The Dynamical Landscape of Reservoir Computing with Elementary Cellular Automata 

      Glover, Tom Eivind; Lind, Pedro; Yazidi, Anis; Osipov, Evgeny; Nichele, Stefano (Conference object, 2021)
      Reservoir Computing with Cellular Automata (ReCA) is a promising concept by virtue of its potential for efficient hardware implementation and theoretical understanding of Cellular Auotmata (CA). However, ReCA has so far ...

    • EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality 

      Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Lecture Notes in Computer Science;Volume 12104, Conference object, 2020-04-09)
      Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ...

    • Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity 

      Jensen Farner, Jørgen; Weydahl, Håkon; Jahren, Ruben; Huse Ramstad, Ola; Nichele, Stefano; Heiney, Kristine Anne (IEEE Symposium Series on Computational Intelligence (SSCI);2021 IEEE Symposium Series on Computational Intelligence (SSCI), Conference object, 2021-01-24)
      Neuro-inspired models and systems have great potential for applications in unconventional computing. Often, the mechanisms of biological neurons are modeled or mimicked in simulated or physical systems in an attempt to ...

    • Reservoir Computing Using Nonuniform Binary Cellular Automata 

      Nichele, Stefano; Gundersen, Magnus Skogstrøm (Complex Systems;Volume 26, Issue 3, Journal article; Peer reviewed, 2017)
      The reservoir computing (RC) paradigm utilizes a dynamical system (a reservoir) and a linear classifier (a readout layer) to process data from sequential classification tasks. In this paper, the usage of cellular automata ...

    • Universality of Evolved Cellular Automata in-Materio 

      Nichele, Stefano; Farstad, Sigve Sebastian; Tufte, Gunnar (Journal article; Peer reviewed, 2017)
      Evolution-in-Materio (EIM) is a method of using artificial evolution to exploit physical properties of materials for computation. It has previously been successfully used to evolve a multitude of different computational ...