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Articles by Shi-Ze Guo
Total Records ( 3 ) for Shi-Ze Guo
  Chong Li , Shi-Ze Guo , Zhe-Ming Lu and Yu-Long Qiao
  Complex network is a young and booming research area, which makes people know more about the characteristic of complex systems and get deeper acquaintanceship about nature. As randomness is a common characteristic of many real-life complex systems, people take a long time to research it and constructed many stochastic models. However, these models still cannot make people clear how the complex network is formed vividly step by step. Therefore, deterministic models have attracted considerable interests for their topological features can be analytically obtained. Swirl is a common natural phenomenon, which has attracted much attention in recent years. In this study, inspired by the swirl phenomenon, a deterministic model is first constructed to describe swirl-shaped networks and then both analytical solutions and experimental results are presented for the topological characteristics of the proposed model. The results demonstrate that the proposed model is a constant-degree centrosymmetric network with a high clustering coefficient.
  Zheng-Liang Huang , Shi-Ze Guo and Zhe-Ming Lu
  This study presents to construct special networks from images and then apply their topological properties to image retrieval. Each input color image is divided into three separate gray-level images in the RGB space. For each gray-level image, we view the 256 gray-levels as nodes and construct the Horizontal Gray-level Co-occurrence Network (HGCN) and Vertical Gray-level Co-occurrence Network (VGCN) by counting the number of horizontal and vertical occurrences for each possible gray-level pair. Based on the obtained six directed weighted networks HGCN_R/G/B and VGCN_R/G/B, we extract their topological features including in-degrees, out-degrees, in-strengths and out-strengths for image retrieval. Simulation results demonstrate the superiority of our features to some existing features in terms of P-R curve.
  Xin-Feng Li , Shi-Ze Guo , Yu-Xin Su and Zhe-Ming Lu
  Recently, researchers have presented several deterministic small-world networks (DSWNs) which can be generated in a special iteration process without randomness. However, to the best of our knowledge, no one has studied the synchronizability of DSWNs up to now. In this study, we focus on the synchronizability of the edge iteration based deterministic small world network (EIB-DSWN) that was presented in 2006. Our testing results show that the EIB-DSWN has very poor synchronizability. To improve the synchronizability, we propose using the Modified Simulated Annealing (MSA) algorithm to optimize the EIB-DSWN. After MSA-based optimization, to check if the optimized network is still a kind of small-world network, we calculate its three main characteristics. It turns out that the MSA algorithm can significantly optimize the synchronizability of the EIB-DSWN under the premise of ensuring small world characteristics.
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