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政大機構典藏 > 理學院 > 應用數學系 > 期刊論文 > Item 140.119/130198

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題名:	On the monotonicity of entropy for multilayer cellular neural networks
作者:	班榮超 Ban, Jung-Chao Chang, Chih-Hung
貢獻者:	應數系
關鍵詞:	Cellular neural networks;soﬁc shift;topological entropy;forcing relation;maximaltemplate;minimal template
日期:	2009-11
上傳時間:	2020-06-22 13:42:07 (UTC+8)
摘要:	This work investigates the monotonicity of topological entropy for one-dimensional multilayer cellular neural networks. The interacting radius and number of layers are treated as parameters. Fix either one of them; the set of topological entropies grows as a strictly nested sequence with respect to one another. Apart from the comparison of the set of topological entropies, maximal and minimal templates are indicators of a dynamical system. Our results demonstrate that maximal and minimal templates of larger interacting radius (respectively number of layers) dominate those of smaller one. To be precise, the strict monotonicity of topological entropy is demonstrated through the comparison of the maximal and minimal templates as the parameters are varied.
關聯:	International Journal of Bifurcation and Chaos, Vol.19, No.11, pp.3657-3670
資料類型:	article
DOI 連結:	https://doi.org/10.1142/S0218127409025043
DOI:	10.1142/S0218127409025043
顯示於類別:	[應用數學系] 期刊論文

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