The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Cellular neural networks: applications
Abstract
The theory of a novel class of information-processing systems, called cellular neural networks, which are capable of high-speed parallel signal processing, was presented in a previous paper (see ibid., vol.35, no.10, p.1257-72, 1988). A dynamic route approach for analyzing the local dynamics of this class of neural circuits is used to steer the system trajectories into various stable equilibrium configurations which map onto binary patterns to be recognized. Some applications of cellular neural networks to such areas as image processing and pattern recognition are demonstrated, albeit with only a crude circuit. In particular, examples of cellular neural networks which can be designed to recognize the key features of Chinese characters are presented.>
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Cites
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The graph neural network model
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Short-term plasticity and long-term potentiation mimicked in single inorganic synapses
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On recent advances in PV output power forecast
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CrossNets: High‐Performance Neuromorphic Architectures for CMOL Circuits
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Metadata
- Authors
- Chua, L. O., & Yang, L.
- Venue
- IEEE Transactions on Circuits and Systems
- Published
- 1988-10
- Volume
- 35
- Issue
- 10
- Pages
- 1273-1290
- ISSN
- 0098-4094 (ISSN-L)
- 1558-1276
- OpenAlex
- W2056717940
- Cited by
- 2,375
- References
- 11
- FWCI
- 7.87
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
