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Chemical implementation of neural networks and Turing machines.
Open accessAbstract
We propose a reversible reaction mechanism with a single stationary state in which certain concentrations assume either high or low values dependent on the concentration of a catalyst. The properties of this mechanism are those of a McCulloch-Pitts neuron. We suggest a mechanism of interneuronal connections in which the stationary state of a chemical neuron is determined by the state of other neurons in a homogeneous chemical system and is thus a "hardware" chemical implementation of neural networks. Specific connections are determined for the construction of logic gates: AND, NOR, etc. Neural networks may be constructed in which the flow of time is continuous and computations are achieved by the attainment of a stationary state of the entire chemical reaction system, or in which the flow of time is discretized by an oscillatory reaction. In another article, we will give a chemical implementation of finite state machines and stack memories, with which in principle the construction of a universal Turing machine is possible.
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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
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Szaciłowski, K. (2008) · Chemical Reviews · doi:10.1021/cr068403q · Cited by 827
Nonlinear Chemical Dynamics: Oscillations, Patterns, and Chaos
Epstein, I. R., & Showalter, K. (1996) · The Journal of Physical Chemistry · doi:10.1021/jp953547m · Cited by 542
Sterling, P., & Laughlin, S. (2015) · doi:10.7551/mitpress/9780262028707.001.0001 · Cited by 482
Artificial Chemistries—A Review
Dittrich, P., Ziegler, J., & Banzhaf, W. (2001) · Artificial Life · doi:10.1162/106454601753238636 · Cited by 423
Metadata
- Authors
- Hjelmfelt, A., Weinberger, E. D., & Ross, J.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 1991-12-15
- Volume
- 88
- Issue
- 24
- Pages
- 10983-10987
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1996197315
- Cited by
- 256
- References
- 2
- FWCI
- 0.76
- Type
- journal article
- Language
- en
- Open access
- green
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- Hjelmfelt, A., Weinberger, E. D., & Ross, J. (1991). Chemical implementation of neural networks and Turing machines. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.88.24.10983
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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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