Abstract
As it was stated in [113], some autonomous CNNs represent an excellent approximation to the nonlinear partial diffrential equations (PDEs). Although the 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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© 2003 Springer Science+Business Media Dordrecht
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Slavova, A. (2003). CNN modelling in biology, physics and ecology. In: Cellular Neural Networks: Dynamics and Modelling. Mathematical Modelling: Theory and Applications, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-0261-4_4
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DOI: https://doi.org/10.1007/978-94-017-0261-4_4
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-6254-3
Online ISBN: 978-94-017-0261-4
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