Abstract
PCNN-Pulse Coupled Neural Network, a new artificial neural network based on biological experimental results, can be widely used for image processing. The complexities of the PCNN’s structure and its dynamical behaviors limit its application so simplification of PCNN is necessary. We have used simplified PCNNs to efficiently process image. In this paper dynamical behaviors of simplified PCNNs under certain conditions are analyzed in detail and we obtain the conclusion that under these conditions, simplified PCNNs have periodic solutions, i.e. their dynamical behaviors are periodical.
This research was supported by China Postdoctoral Science Foundation (No.2003034282) and National Natural Science Foundation of China (No.60171036 and No.30370392).
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© 2004 Springer-Verlag Berlin Heidelberg
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Gu, X., Zhang, L., Yu, D. (2004). Simplified PCNN and Its Periodic Solutions. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks – ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28647-9_5
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DOI: https://doi.org/10.1007/978-3-540-28647-9_5
Publisher Name: Springer, Berlin, Heidelberg
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