| dc.contributor | 應數系 | - |
| dc.creator (作者) | 班榮超 | - |
| dc.creator (作者) | Ban, Jung-Chao | - |
| dc.creator (作者) | Chang, Chih-Hung | - |
| dc.creator (作者) | Lin, Song-Sun | - |
| dc.creator (作者) | Lin, Yin-Heng | - |
| dc.date (日期) | 2009-01 | - |
| dc.date.accessioned | 22-Jun-2020 13:43:25 (UTC+8) | - |
| dc.date.available | 22-Jun-2020 13:43:25 (UTC+8) | - |
| dc.date.issued (上傳時間) | 22-Jun-2020 13:43:25 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/130204 | - |
| dc.description.abstract (摘要) | This study investigates the complexity of the global set of output patterns for one-dimensional multi-layer cellular neural networks with input. Applying labeling to the output space produces a sofic shift space. Two invariants, namely spatial entropy and dynamical zeta function, can be exactly computed by studying the induced sofic shift space. This study gives sofic shift a realization through a realistic model. Furthermore, a new phenomenon, the broken of symmetry of entropy, is discovered in multi-layer cellular neural networks with input. | - |
| dc.format.extent | 490078 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Journal of Differential Equations, Vol.246, No.2, pp.552-580 | - |
| dc.subject (關鍵詞) | Learning problem | - |
| dc.title (題名) | Spatial complexity in multi-layer cellular neural networks | - |
| dc.type (資料類型) | article | - |
| dc.identifier.doi (DOI) | 10.1109/CNNA.2010.5430257 | - |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1109/CNNA.2010.5430257 | - |
