ON THE DENSE ENTROPY OF TWO-DIMENSIONAL INHOMOGENEOUS CELLULAR NEURAL NETWORKS

doi:10.1142/S0218127408022378

完整後設資料紀錄

DC 欄位	值	語言
dc.contributor.author	Ban, Jung-Chao	en_US
dc.contributor.author	Chang, Chih-Hung	en_US
dc.date.accessioned	2014-12-08T15:10:45Z	-
dc.date.available	2014-12-08T15:10:45Z	-
dc.date.issued	2008-11-01	en_US
dc.identifier.issn	0218-1274	en_US
dc.identifier.uri	http://dx.doi.org/10.1142/S0218127408022378	en_US
dc.identifier.uri	http://hdl.handle.net/11536/8228	-
dc.description.abstract	This investigation elucidates the dense entropy of two-dimensional inhomogeneous cellular neural networks (ICNN) with/without input. It is strongly related to the learning problem (or inverse problem); the necessary and sufficient conditions for the admissibility of local patterns must be characterized. For ICNN with/without input, the entropy function is dense in [ 0, log 2] with respect to the parameter space and the radius of the interacting cells, indicating that, in some sense, ICNN exhibit a wide range of phenomena.	en_US
dc.language.iso	en_US	en_US
dc.subject	Entropy	en_US
dc.subject	learning problem	en_US
dc.subject	ICNN	en_US
dc.title	ON THE DENSE ENTROPY OF TWO-DIMENSIONAL INHOMOGENEOUS CELLULAR NEURAL NETWORKS	en_US
dc.type	Article	en_US
dc.identifier.doi	10.1142/S0218127408022378	en_US
dc.identifier.journal	INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS	en_US
dc.citation.volume	18	en_US
dc.citation.issue	11	en_US
dc.citation.spage	3221	en_US
dc.citation.epage	3231	en_US
dc.contributor.department	應用數學系	zh_TW
dc.contributor.department	Department of Applied Mathematics	en_US
dc.identifier.wosnumber	WOS:000262599200003	-
dc.citation.woscount	0	-
顯示於類別：	期刊論文

文件中的檔案：

000262599200003.pdf

若為 zip 檔案，請下載檔案解壓縮後，用瀏覽器開啟資料夾中的 index.html 瀏覽全文。