| ID | 原文 | 译文 |
| 10524 | 该算法通过优化像素置乱、像素替换和密文扩散过程进一步混淆明文图像和密文图像的关系,并通过引入新的超混沌序列量化方法,减少超混沌系统的迭代次数,提高运行效率。 | Through optimizing the algorithm pixel scrambling, pixel replacement and ciphertext diffusion process further confusing the relationship between the plaintext and ciphertext images, and by introducing a new hyperchaos sequence of quantitative methods, reduce the number of iterations hyperchaos system, improve the operation efficiency. |
| 10525 | 实验仿真结果表明,算法具有很高的安全性和实用性,可广泛运用于图像保密通信等领域。 | The experimental simulation results show that the algorithm has high security and practicability, which can be widely used in fields such as image encryption communication. |
| 10526 | 快速同时定位与建图(fast simultaneous localization and mapping,FastSLAM)算法的采样过程会带来粒子退化问题,为了改进算法的性能,提高估计精度,从研究粒子滤波的建议分布函数出发,提出基于自适应渐消扩展卡尔曼滤波(adaptive fading extended Kalman filter,AFEKF)的FastSLAM算法。 | Rapid positioning and built figure (fast simultaneous localization and mapping, FastSLAM) algorithm of sampling process brings particle degradation problems, in order to improve the performance of the algorithm, improve the estimation precision, from studying the proposal distribution function of particle filter, is proposed based on adaptive fading extended Kalman filter (the adaptive fading extended Kalman filter, AFEKF) FastSLAM algorithm. |
| 10527 | 该算法基于FastSLAM的基本框架,利用AFEKF产生一种参数可自适应调节的建议分布函数,使其更接近移动机器人的后验位姿概率分布,减缓粒子集的退化。 | The algorithm based on the fundamental framework of the FastSLAM, parameters can be adjusted adaptive AFEKF to produce a proposal distribution function, make it more close to the posterior position of the mobile robot probability distribution, slow degradation of particle set. |
| 10528 | 因此在同等粒子数的情况下,该算法有效提高了SLAM精度,以此减少所使用的粒子数,降低算法的复杂度。 | Therefore, under the same number of particles, the algorithm effectively improves the precision of SLAM, to reduce the use of particle number, reduce the complexity of the algorithm. |
| 10529 | 基于模拟器和标准数据集的实验仿真结果验证了该算法的有效性。 | Based on a simulator and standard data sets of the experimental simulation results show the effectiveness of the algorithm. |
| 10530 | 提出了一种基于模糊双门限的地波雷达与船只身份自动识别系统(automatic identification system,AIS)目标航迹关联方法。 | A ground wave radar based on fuzzy double threshold identity with the ship automatic identification system (automatic identification system, AIS) of target correlation method. |
| 10531 | 该方法主要是利用模糊隶属度来描述两条航迹间的关联程度,并通过双门限检测来确定关联的航迹对。 | This method is mainly by using fuzzy membership degree to describe the degree of correlation between two tracks, and through the double threshold detection to determine the associated track. |
| 10532 | 具体讨论分析了算法中展度、权重、调整因子等参数的选取原则,最后利用2011年10月31和2013年9月6日获取的两批实测地波雷达与AIS数据将本文方法与最近邻航迹关联算法做了对比。 | Specific discussion brought the degree of the algorithm is analyzed, weight, adjusting factor selection of parameters, such as the principle, the final use of October 31, 2011 and September 6, 2013 to obtain two batch of measured ground wave radar and AIS data to the method and made a comparison of nearest neighbor correlation algorithm. |
| 10533 | 结果表明,此方法的关联率高于最近邻航迹关联算法,并且在航迹较为复杂情况下,提出的航迹关联算法具有更好的稳定性。 | The results show that this method of connection rate is higher than of nearest neighbor correlation algorithm, and under the condition of track is more complex, the correlation algorithm has better stability. |