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On Information Proc...
On Information Processing with Networks of Nano-Scale Switching Elements
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- Konkoli, Zoran, 1966 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Wendin, Göran, 1942 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2014
- 2014
- Engelska.
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Ingår i: International Journal of Unconventional Computing. - 1548-7199 .- 1548-7202. ; 10:5-6, s. 405-428
- Relaterad länk:
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https://research.cha...
Abstract
Ämnesord
Stäng
- Unconventional computing explores multi-scale platforms connecting molecular-scale devices into networks for the development of scalable neuromorphic architectures, often based on new materials and components with new functionalities. We review some work investigating the functionalities of locally connected networks of different types of switching elements as computational substrates. In particular, we discuss reservoir computing with networks of nonlinear nanoscale components. In usual neuromorphic paradigms, the network synaptic weights are adjusted as a result of a training/learning process. In reservoir computing, the non-linear network acts as a dynamical system mixing and spreading the input signals over a large state space, and only a readout layer is trained. We illustrate the most important concepts with a few examples, featuring memristor networks with time-dependent and history dependent resistances.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- MOLECULAR ELECTRONICS
- LIQUID-STATE MACHINE
- SYSTEMS
- LOGIC GATES
- molecular network
- MEMRISTIVE DEVICES
- MEMORY
- Reservoir computing
- RECURRENT NEURAL-NETWORKS
- JUNCTIONS
- CONNECTIVITY
- COMPUTATION
- memristor
- dynamic system
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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