| 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.date (日期) | 2019-05 | |
| dc.date.accessioned | 28-Apr-2020 13:54:34 (UTC+8) | - |
| dc.date.available | 28-Apr-2020 13:54:34 (UTC+8) | - |
| dc.date.issued (上傳時間) | 28-Apr-2020 13:54:34 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/129555 | - |
| dc.description.abstract (摘要) | This paper investigates the coloring problem on Fibonacci-Cayley tree, which is a Cayley graph whose vertex set is the Fibonacci sequence. More precisely, we elucidate the complexity of shifts of finite type defined on Fibonacci-Cayley tree via an invariant called entropy. We demonstrate that computing the entropy of a Fibonacci tree-shift of finite type is equivalent to studying a nonlinear recursive system and reveal an algorithm for the computation. What is more, the entropy of a Fibonacci tree-shift of finite type is the logarithm of the spectral radius of its corresponding matrix. We apply the result to neural networks defined on Fibonacci-Cayley tree, which reflect those neural systems with neuronal dysfunction. Aside from demonstrating a surprising phenomenon that there are only two possibilities of entropy for neural networks on Fibonacci-Cayley tree, we address the formula of the boundary in the parameter space. | |
| dc.format.extent | 304665 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Journal of Algebra Combinatorics Discrete Structures and Applications, Vol.6, No.2, pp.105-122 | |
| dc.subject (關鍵詞) | Neural networks ; Learning problem ; Cayley tree ; Separation property, Entropy | |
| dc.title (題名) | Complexity of neural networks on Fibonacci-Cayley tree | |
| dc.type (資料類型) | article | |
