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Cellular Neural Networks and Visual Computing: Foundations and Applications
Abstract
Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed and are paving the way to an analog computing industry. This unique undergraduate level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of disciplines. Although its prime focus is on visual computing, the concepts and techniques described in the book will be of great interest to those working in other areas of research including modeling of biological, chemical and physical processes. Leon Chua, co-inventor of the CNN, and Tamás Roska are both highly respected pioneers in the field.
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Citations
Cited by
MEMRISTOR CELLULAR AUTOMATA AND MEMRISTOR DISCRETE-TIME CELLULAR NEURAL NETWORKS
ITOH, M., & CHUA, L. O. (2009) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127409025031 · Cited by 299
Self-citationWen, S., Zeng, Z., Huang, T., & Zhang, Y. (2014) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2013.2294855 · Cited by 289
Circuit design and exponential stabilization of memristive neural networks
Wen, S., Huang, T., Zeng, Z., Chen, Y., & Li, P. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.10.011 · Cited by 178
Collective intelligence for deep learning: A survey of recent developments
Ha, D., & Tang, Y. (2022) · Collective Intelligence · doi:10.1177/26339137221114874 · Cited by 71
Metadata
- Authors
- Chua, L. O., & Roska, T.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2002-05-23
- OpenAlex
- W1570173134
- Cited by
- 558
- References
- 0
- FWCI
- 6.21
- Type
- book
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.