The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Cellular neural networks: theory
Abstract
A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear analog circuits that process signals in real time. Like cellular automata, they consist of a massive aggregate of regularly spaced circuit clones, called cells, which communicate with each other directly only through their nearest neighbors. Each cell is made of a linear capacitor, a nonlinear voltage-controlled current source, and a few resistive linear circuit elements. Cellular neural networks share the best features of both worlds: their continuous-time feature allows real-time signal processing, and their local interconnection feature makes them particularly adapted for VLSI implementation. Cellular neural networks are uniquely suited for high-speed parallel signal processing.>
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Cites
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
Hopfield, J. J. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.10.3088 · Cited by 6,918
Associative recall of memory without errors
Kanter, I., & Sompolinsky, H. (1987) · Physical Review A · doi:10.1103/physreva.35.380 · Cited by 379
Cited by
The graph neural network model
Scarselli, F., Gori, M., Tsoi, A. C., Hagenbuchner, M., & Monfardini, G. (2009) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2008.2005605 · Cited by 9,582
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
Sherstinsky, A. (2020) · Physica D: Nonlinear Phenomena · doi:10.1016/j.physd.2019.132306 · Cited by 5,680
Cellular neural networks: applications
Chua, L. O., & Yang, L. (1988) · IEEE Transactions on Circuits and Systems · doi:10.1109/31.7601 · Cited by 2,375
Self-citationThe future of electronics based on memristive systems
Zidan, M. A., Strachan, J. P., & Lu, W. D. (2018) · Nature Electronics · doi:10.1038/s41928-017-0006-8 · Cited by 2,138
Global convergence of neural networks with discontinuous neuron activations
Forti, M., & Nistri, P. (2003) · IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications · doi:10.1109/tcsi.2003.818614 · Cited by 451
Metadata
- Authors
- Chua, L. O., & Yang, L.
- Venue
- IEEE Transactions on Circuits and Systems
- Published
- 1988-10
- Volume
- 35
- Issue
- 10
- Pages
- 1257-1272
- ISSN
- 0098-4094 (ISSN-L)
- 1558-1276
- OpenAlex
- W2160121923
- Cited by
- 4,769
- References
- 3
- FWCI
- 16.98
- 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.
