ID 原文 译文
24085 该文给出了一个新的二次多项式混沌系统，并利用系统与 Tent 映射拓扑共轭的性质，给出了系统的概率密度函数，基于概率密度的形式，进一步设计了一个变换函数，实现了系统的均匀化。 A new quadratic polynomial chaotic system is given and homogenized based on its probability density function.
24086 针对均匀化前后的混沌系统构造了 S 盒生成算法，对该算法产生的 300 个 S 盒进行差分概率(DP)和线性概率(LP)的统计分析，结果表明均匀化后混沌系统产生的 S 盒的 DP 和 LP 略优于均匀化前的值。 Then, based on the chaotic systems before and after homogenization, an S-box generation algorithm is constructed. By numerical simulation, the algorithm dynamically generates 300 S-boxes and then analyses their Differential Probability (DP) and Linear Probability (LP). The statistical results show that the uniform chaotic system can produce better performance of S-boxes.
24087 针对移动 Ad hoc 网络动态拓扑特性，该文提出一种以可靠路径稳定度估计为基础的多路径路由优化算法。 To deal with dynamic network topology in Mobile Ad hoc NETworks (MANETs), a reliability-enhanced multipath source routing algorithm is proposed based on accurate path stability estimation.
24088 该算法从路径剩余生存期统计特性出发，充分考虑相邻链路生存期相关性，从而消除已有算法在路径稳定度估计中存在的理论误差，并利用优化后的稳定度准则实现路由发现进程的多路径选取和基于备用路径支持的快速路由修复。 In order to eliminate theoretical errors existing in current approaches, statistical properties of residual path lifetime are exploited by fully introducing correlation among neighboring links' residual link lifetime. Optimized link and path stability metric is then provided to realize a multipath-enabled routing discovery procedure and a backup path-support fast routing recovery mechanism.
24089 仿真对比结果表明，该算法具有较快的收敛速度，能够有效提高网络吞吐量，缩短数据传输时延并降低路由开销，更好地保证较高节点移动度下的数据传输稳定性。 Simulation results show that the proposed routing algorithm can achieve fast routing discovery convergence, increase network throughput, reduce data transmission delay, and lower routing overhead. Furthermore, high network reliability can be well guaranteed even under high node mobility degree.
24090 多径干扰是高精度定位的主要误差源，估计多径参数对消除多径误差，提高导航系统定位精度具有重要意义。 Multipath is the dominant error source for high-accuracy positioning systems. It is significant for eliminating the multipath error and improving the positioning accuracy to estimate multipath parameters.
24091 针对扩展 Kalman 滤波(EKF)在进行多径参数估计时，存在对初值敏感，估计结果在真值附近具有较大波动的缺点，该文提出一种基于粒子滤波(PF)和滑动平均 EKF 的多径估计算法。 There are two main disadvantages for multipath parameters estimation by using the Extended Kalman Filter (EKF): it is sensitive to the initial value; filtering results fluctuate obviously around actual values. To solve these problems, an improved multipath estimation algorithm based on Particle Filter (PF) and sliding average EKF is proposed.
24092 该算法首先利用 PF 得到多径参数的粗略估计值，并将该值作为 EKF 的初始估计值，以克服 EKF 对初值敏感的问题。 Firstly, PF is used to obtain rough estimation values of multipath parameters, which are set as initial estimations for EKF to reduce the initial value sensitivity.
24093 接着对 EKF 的估计结果进行滑动平均，并将平均后的滤波结果作为多径参数的估计结果。 Then, the EKF filtering results are smoothed by sliding average. The smoothing results are outputted as the multipath estimation.
24094 仿真结果表明，改进后的多径估计算法可有效降低估计结果的波动幅度，同时解决了 EKF 对初值敏感的问题。 The simulation results show that the estimation results of the proposed algorithm have smaller fluctuation magnitude compared with EKF, and it is insensitive to the initial estimation.