| Presentation | 2012-01-26 Comparison and Evaluation of Growing Complex Network Generated by Similarities Keisuke TERAYAMA, Yukari YAMAUCHI, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We proposed a method to configure growing network based on similarities. Generated network by the proposed method shows small characteristics path length (L), large clustering coefficient (C) and the power-law degree distribution. In this paper, the network generated by the proposed method examined through simulations of associative memories using three types of training patterns, random, sequential and characteristic. The result shows that the hub nodes have a significant effect to storage capacity. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Complex Network / Self-Organization / Small World / Associative Memory |
| Paper # | NC2011-103 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2012/1/19(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Comparison and Evaluation of Growing Complex Network Generated by Similarities |
| Sub Title (in English) | |
| Keyword(1) | Complex Network |
| Keyword(2) | Self-Organization |
| Keyword(3) | Small World |
| Keyword(4) | Associative Memory |
| 1st Author's Name | Keisuke TERAYAMA |
| 1st Author's Affiliation | College of Industrial Technology, Nihon University() |
| 2nd Author's Name | Yukari YAMAUCHI |
| 2nd Author's Affiliation | College of Industrial Technology, Nihon University |
| Date | 2012-01-26 |
| Paper # | NC2011-103 |
| Volume (vol) | vol.111 |
| Number (no) | 419 |
| Page | pp.pp.- |
| #Pages | 6 |
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