Topological Properties of Fibonacci Networks

The Fibonacci numbers are the numbers defined by the linear recurrence equation,in which each subsequent number is the sum of the previous two.In this paper,we propose Fibonacci networks using Fibonacci numbers.The analytical expressions involving degree distribution,average path length and mean first passage time are obtained.This kind of networks exhibits the small-world characteristic and follows the exponential distribution.Our proposed models would provide the valuable insights into the deterministically delayed growing networks.     

气泡幕后向散射光信号特性的蒙特卡罗方法研究

利用蒙特卡罗方法对水介质中的气泡幕的后向光散射回波信号进行了系统仿真。通过对计算结果与实验结果的比较,证明了蒙特卡罗方法的有效性。根据仿真结果,结合理论分析的方法,对气泡幕位置、厚度和接收器视场角等参数对回波信号的影响进行了分析,结果表明:回波信号出现时间与气泡幕位置存在一一对应的关系;在气泡幕的衰减系数ρσt不变的情况下,存在一个有效气泡幕厚度,当大于该厚度时,气泡幕的后向光散射回波信号基本不变;在系统各项参数不变的情况下,适当增加接收器的视场角,可有效地提高回波信号的信噪比。     

基于时间尺度域二维相关的宽带信号检测

按相关检测的思想,提出了基于小波变换(CWT)时间尺度域二维相关的宽带水声信号检测方法,并对其检测性能进行了仿真与实验分析,结果表明:基于CWT的检测器检测性能优于能量检测器,与匹配滤波器相比差别不是很大,而且基于CWT的检测器有很好的鲁棒性,特别是在低信噪比下的检测性能尤其突出。该方法不仅仅适合于宽带水声处理,也适合于处理波形和达到时间未知的暂态声呐、雷达及鱼雷自导等信号。     

Exact scaling for the mean first-passage time of random walks on a generalized Koch network with a trap

In this paper,we study the scaling for the mean first-passage time(MFPT) of the random walks on a generalized Koch network with a trap.Through the network construction,where the initial state is transformed from a triangle to a polygon,we obtain the exact scaling for the MFPT.We show that the MFPT grows linearly with the number of nodes and the dimensions of the polygon in the large limit of the network order.In addition,we determine the exponents of scaling efficiency characterizing the random walks.Our results are the generalizations of those derived for the Koch network,which shed light on the analysis of random walks over various fractal networks.     

Random walks in generalized delayed recursive trees

Recently a great deal of effort has been made to explicitly determine the mean first-passage time （MFPT） between two nodes averaged over all pairs of nodes on a fractal network. In this paper, we first propose a family of generalized delayed recursive trees characterized by two parameters, where the existing nodes have a time delay to produce new nodes. We then study the MFPT of random walks on this kind of recursive tree and investigate the effect of the time delay on the MFPT. By relating random walks to electrical networks, we obtain an exact formula for the MFPT and verify it by numerical calculations. Based on the obtained results, we further show that the MFPT of delayed recursive trees is much shorter, implying that the efficiency of random walks is much higher compared with the non-delayed counterpart. Our study provides a deeper understanding of random walks on delayed fractal networks.     

Exact scaling for the mean first-passage time of random walks on a generalized Koch network with a trap

In this paper, we study the scaling for the mean first-passage time (MFPT) of the random walks on a generalized Koch network with a trap. Through the network construction, where the initial state is transformed from a triangle to a polygon, we obtain the exact scaling for the MFPT. We show that the MFPT grows linearly with the number of nodes and the dimensions of the polygon in the large limit of the network order. In addition, we determine the exponents of scaling efficiency characterizing the random walks. Our results are the generalizations of those derived for the Koch network, which shed light on the analysis of random walks over various fractal networks.