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Non-linear Neuro-inspired Circuits and Systems: Processing and Learning Issues

  • Luca Patanè
  • Roland Strauss
  • Paolo ArenaEmail author
Chapter
  • 457 Downloads
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Abstract

In this chapter the main elements useful for the design and realization of the neural architectures reported in the following chapters will be presented. Considering spiking and non-spiking neurons, the models used for implementing each of them, the synaptic models, the basic learning and plasticity algorithms and the network architectures will be introduced and analysed. The key elements that led to their selection and application in the developed neuro-inspired systems will be discussed briefly.

Keywords

Synaptic Model Echo State Networks (ESN) Mushroom Bodies Reservoir Computing Liquid State Machine (LSM) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2018

Authors and Affiliations

  1. 1.Dipartimento di Ingegneria Elettrica Elettronica e dei SistemiUniversity of CataniaCataniaItaly
  2. 2.Institut für Entwicklungsbiologie und NeurobiologieJohannes Gutenberg Universität MainzMainzGermany

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