中文摘要：

研究具有一个吸收点的广义伪分形网络上随机游走的平均首达时间．广义伪分形网络的显著特点是在每一次迭代中，每条现有的边会产生有限个节点．根据网络的演化算法，得到了平均首达时间的精确表达式．当网络的阶数足够大时，平均首达时间是按照网络节点数的幂律在增长．此外，可以通过改变网络参数来改善此类网络的随机游走的效率．这些研究结果是对伪分形网络相应结果的推广，将为深入研究各类分形网络的随机游走提供帮助．

英文摘要：

The scaling of mean first-passage time （MFPT） for random walks on the generalized pseudofractal web （GPFW） with a trap is studied. The feature of the GPFW is that every existing edge produces finite nodes in each evolution step. Through the web construction, the exact scaling for the MFPT is obtained. The MPFT grows as a power-law function with the number of nodes in the large limit of network order. In addition, the efficiency of random walks on this kind of web can be improved through changing the network parameter. These results are generalizations of those derived for the pseudofractal web, which shed some lights on the analysis of random walks over various fractal networks.