The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
An Electronic Version of Pavlov's Dog
Abstract
Neuromorphic plasticity is the basic platform for learning in biological systems and is considered as the unique concept in the brains of vertebrates, which outperform today's most powerful digital computers when it comes to cognitive and recognition tasks. An emerging task in the field of neuromorphic engineering is to mimic neural pathways via elegant technological approaches to close the gap between biological and digital computing. In this respect, functional, memristive devices are considered promising candidates with yet unknown benefit for neuromorphic circuits. It is demonstrated that a single Pt/Ge 0.3 Se 0.7/SiO 2/Cu memristive device implemented in an analogue circuitry mimics non‐associative and associative types of learning. For Pavlovian conditioning, different threshold voltages for the memristive device and the comparator are essential. Similarities to neurobiological correlates of learning are discussed in the framework of hebbian learning rule, plasticity, and long‐term potentiation.
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Cites
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Cited by
Training and operation of an integrated neuromorphic network based on metal-oxide memristors
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Nonvolatile ferroelectric domain wall memory
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Metadata
- Authors
- Ziegler, M., Soni, R., Patelczyk, T., Ignatov, M., Bartsch, T., Meuffels, P., & Kohlstedt, H.
- Venue
- Advanced Functional Materials
- Publisher
- Wiley
- Published
- 2012-04-10
- Volume
- 22
- Issue
- 13
- Pages
- 2744-2749
- ISSN
- 1616-301X (ISSN-L)
- 1616-3028
- OpenAlex
- W2092020760
- Cited by
- 206
- References
- 12
- FWCI
- 9.97
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ziegler, M., Soni, R., Patelczyk, T., Ignatov, M., Bartsch, T., Meuffels, P., & Kohlstedt, H. (2012). An Electronic Version of Pavlov's Dog. Advanced Functional Materials. https://doi.org/10.1002/adfm.201200244
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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