Titlebook: Cellular Neural Networks: Dynamics and Modelling; Angela Slavova Book 2003 Springer Science+Business Media Dordrecht 2003 information proc

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1386-2960 new computation model, called Neural Networks, has been proposed, which is based on some aspects of neurobiology and adapted to integrated circuits. The increased availability of com- puting power has not only made many new applications possible but has also created the desire to perform cognitive t

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mechanical

Basic theory about CNNs, emergence or complexity. They share a common unifying principle of dynamic arrays, namely, interconnections of a sufficiently large number of simple dynamic units can exibit extremely complex and self-organizing behaviors.

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https://doi.org/10.1007/978-3-540-39567-6have clear physical meanings. Finally, the method’s complexity only increases mildly with system order. Frequency domain analysis, however cannot be directly applied to nonlinear systems because frequency response functions cannot be defined for nonlinear systems.

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Appendix C. Describing function method and its application for analysis of Cellular Neural Networkshave clear physical meanings. Finally, the method’s complexity only increases mildly with system order. Frequency domain analysis, however cannot be directly applied to nonlinear systems because frequency response functions cannot be defined for nonlinear systems.

indignant

1386-2960 lass of information processing systems, which posseses some of the key fea- tures of neural networks (NNs) and which has important potential applications in suc978-90-481-6254-3978-94-017-0261-4Series ISSN 1386-2960

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Basic theory about CNNs,he zebra get its stripes, or how does the fingerprint get its patterns? These phenomena are some manifestations of a multidisciplinary paradigm called emergence or complexity. They share a common unifying principle of dynamic arrays, namely, interconnections of a sufficiently large number of simple

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