Abstract
The pattern recognition using Pulse Coupled Neural Network (PCNN) had been proposed. In conventional studies, the parameters in the PCNN are used to be defined empirically and the optimization of parameters has been known as a remaining problem of PCNN. In this study, we show a method to apply the real coded genetic algorithm to the parameter optimization of the PCNN and we also show performances of pattern recognition by the PCNN with learned parameters.
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References
Echorn, R., et al.: Feature linking via synchronization among distributed assemblies: Simulations of results from cat visual cortex. Neural Computation 2, 293–307 (1990)
Johnson, J.L., Padgett, M.L.: PCNN Models and Applications. IEEE Trans. Neural Network 10(3), 480–498 (1999)
Gu, X., et al.: Object Detection Using Unit-Linking PCNN Image Icons. In: Wang, J., Yi, Z., Żurada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol. 3971, pp. 616–622. Springer, Heidelberg (2006)
Mahgoub, A.G., et al.: An Intersecting Cortical Model Based Framework for Human Face Recognition. J. of Systemics, Cybernetics and Informatics 6(2), 88–93 (2008)
Yonekawa, M., Kurokawa, H.: An automatic parameter adjustment method of Pulse Coupled Neural Network for image segmentation. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds.) ICANN 2009. LNCS, vol. 5768, pp. 399–400. Springer, Heidelberg (2009)
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Yonekawa, M., Kurokawa, H. (2010). The Parameter Optimization of the Pulse Coupled Neural Network for the Pattern Recognition. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15825-4_13
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DOI: https://doi.org/10.1007/978-3-642-15825-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15824-7
Online ISBN: 978-3-642-15825-4
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