Abstract
An efficient simulator for Cellular Neural Networks (CNNs) is presented in this paper. The simulator is capable of performing Raster Simulation for any size of input image, thus a powerful tool for researchers investigating potential applications of CNN. This paper reports an efficient algorithm exploiting the latency properties of Cellular Neural Networks along with popular numerical integration algorithms; simulation results and comparison are also presented.
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© 2004 Springer-Verlag Berlin Heidelberg
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Murgesh, V., Murugesan, K. (2004). Comparison of Numerical Integration Algorithms in Raster CNN Simulation. In: Manandhar, S., Austin, J., Desai, U., Oyanagi, Y., Talukder, A.K. (eds) Applied Computing. AACC 2004. Lecture Notes in Computer Science, vol 3285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30176-9_15
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DOI: https://doi.org/10.1007/978-3-540-30176-9_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23659-7
Online ISBN: 978-3-540-30176-9
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