本文選題：復(fù)雜網(wǎng)絡(luò) + 同步　； 參考：《物理學(xué)報(bào)》2017年06期

【摘要】：大規(guī)模網(wǎng)絡(luò)的同步問(wèn)題是網(wǎng)絡(luò)科學(xué)的重要研究課題之一.粗�；椒ㄌ峁┝艘环N將大規(guī)模網(wǎng)絡(luò)轉(zhuǎn)化為小規(guī)模網(wǎng)絡(luò),同時(shí)又能較好地保持原始網(wǎng)絡(luò)的拓?fù)湫再|(zhì)或動(dòng)態(tài)特性的研究途徑,其中比較有代表性的譜粗�；椒茌^好地保持初始網(wǎng)絡(luò)的同步能力.然而,譜粗�；椒ㄔ趯�(shí)際計(jì)算中計(jì)算量大、對(duì)實(shí)際大規(guī)模網(wǎng)絡(luò)可執(zhí)行性差.本文提出一種改進(jìn)的譜粗粒化算法,能大幅減少計(jì)算量,同時(shí)獲得更好的譜粗�；Ч�.通過(guò)理論分析和大量的數(shù)值仿真實(shí)驗(yàn)驗(yàn)證了所提改進(jìn)算法的粗�；Ч陀�(jì)算量都明顯優(yōu)于原譜粗�；椒�.
[Abstract]:The synchronization of large-scale networks is one of the most important research topics in network science. Coarse-grained method provides a way to transform large scale networks into small scale networks while maintaining the topological or dynamic properties of the original networks. The representative spectral coarse granulation method can maintain the synchronization ability of the initial network. However, the spectral coarse-graining method has a large amount of computation in the actual calculation, and is poor in the performance of the actual large-scale network. In this paper, an improved spectral coarse granulation algorithm is proposed, which can greatly reduce the computational cost and obtain better spectral coarse granulation effect. Through theoretical analysis and a large number of numerical simulation experiments, it is verified that the coarse-graining effect and computational complexity of the proposed improved algorithm are obviously superior to those of the original spectral coarse-graining method.
【作者單位】： 桂林理工大學(xué)理學(xué)院;桂林電子科技大學(xué)數(shù)學(xué)與計(jì)算科學(xué)學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(批準(zhǔn)號(hào):61563013,61663006)資助的課題~~
【分類(lèi)號(hào)】：O157.5

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