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Erschienen in:
Implementing Molecular Logic Gates, Circuits, and Cascades Using DNAzymes Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

19. Memristors in Unconventional Computing: How a Biomimetic Circuit Element Can be Used to Do Bioinspired Computation

verfasst von : Ella Gale

Erschienen in: Advances in Unconventional Computing

Verlag: Springer International Publishing

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Abstract

Memristors differ from resistors by possessing a memory, and both synapses and neurons have been discussed as biological memristors. The short-term memory of the memristor (or spiking profile) is similar in form to neural spikes. Thus, memristors are obvious candidates for building biomimetic circuits and computers. In this chapter, we review some recent experimental results in the area of memritor-based spike computing. We demonstrate how memristor spikes are a real-world memristor model of an inhibitory neuron, then we demonstrate the complex emergent behaviour from networks of memristors which resembles neural dynamics, we then expose these memristor networks to living neural cells, where the memristor state is altered by cellular action. Further investigation of the memristor spiking process allows us to elucidate design rules for spiking logic gates, and we demonstrate a novel full adder instantiated in a single memristor. Spiking memristor computation might be the best route to truly neuromorphic computers.

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Vorheriges Kapitel Organic Memristor Based Elements for Bio-inspired Computing
Nächstes Kapitel Nature-Inspired Computation: An Unconventional Approach to Optimization
Fußnoten
1
Note that there has been some discussion as to whether the memristors have a d.c. response, within which is has been generally agreed that the perfect memristor may not, but non-ideal memristors (which all real devices are) may. This is not a settled issue and generated much discussion at a recent conference (CASFEST 2014).
 
2
Similar to that seen in Fig. 19.15 between 300 and 400 s, and this is a shape not seen in the memristor networks without cells.
 
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Metadaten
Titel
Memristors in Unconventional Computing: How a Biomimetic Circuit Element Can be Used to Do Bioinspired Computation
verfasst von
Ella Gale
Copyright-Jahr
2017
Buch
Advances in Unconventional Computing

Print ISBN: 978-3-319-33920-7

Electronic ISBN: 978-3-319-33921-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-33921-4_19