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

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neutrophils

CNN modelling in biology, physics and ecology,he CNN equations describing reaction-diffusion systems are with the large number of cells, they can exhibit new phenomena that can not be obtained from their limiting PDEs. This demonstrates that an autonomous CNN is in some sense more general than its associated nonlinear PDE.

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Appendix B. Hysteresis and its models,tem whose state is characterized by two scalar variables . and . and we shall assume that they depend continuously on time .. They will play the role of independent and dependent variables, respectively. In the terminology of CNN, they are also named input and output, or also control and state, resp

configuration

Appendix C. Describing function method and its application for analysis of Cellular Neural Networks complex-valued function, the frequency response, instead of differential equation. The power of the method comes from a number of sources. First, graphical representations can be used to facilitate analysis and design. Second, physical insights can be used, because the frequency response functions

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