| ID | 原文 | 译文 |
| 24105 | 该文提出一种基于人工免疫的同步字识别算法，解决了无线网络链路层协议帧同步字的识别问题。 | Inspired by biologic immune system, a novel frame synchronization word identification algorithm based on artificial immune is proposed. |
| 24106 | 算法在定义相关概念的基础上，通过对已知协议类型文件集脱氧核苷酸(ODN)浓度的计算，得到了相关协议的同步字脱氧核苷酸库； | Firstly, due to the calculation of ODN concentration of known protocol type file set, ODN library of synchronization word in corresponding protocol is constructed. |
| 24107 | 然后，利用得到的同步字脱氧核苷酸库与相关文件集进行连续一致匹配，生成同步字检测基因库； | Then, through uniform continuity matching between ODN library of synchronization word and relevant file set, the detecting synchronization word gene library is constructed. |
| 24108 | 最后，利用得到的同步字脱氧核苷酸库和同步字检测基因库，通过连续一致匹配和基因相似度值的计算，实现了同步字的准确识别。 | At last, through calculating similarity value and uniform continuity matching by using ODN library of synchronization word and detecting gene library, synchronization word can be identified exactly. |
| 24109 | 仿真实验验证了算法的有效性，与已有的模式串匹配算法相比，所提算法的鲁棒性较好，具有一定的工程应用价值。 | The new method, which has higher accurate recognition than pattern matching algorithm suggested by simulation results, has significant potential in engineering application. |
| 24110 | 超宽带(Ultra Wide Band, UWB)室内定位系统的定位性能主要受信号非视距(None Line Of Sight, NLOS)传播影响。 | The performance of UWB indoor positioning system is mainly affected by NLOS errors. |
| 24111 | 为此该文提出一种基于信道统计量(Channel Statistics Information, CSI)的信道 NLOS 状态检测法。 | In this paper, a channel state detection method based on channel statistics is proposed. |
| 24112 | 该方法首先在 IEEE802.15.4a 信道模型下对均方根时延扩展和平均超量延迟的概率分布函数进行建模，作为信道标准分布。 | The probability distribution function of Root Mean Square Delay Spread (RMS) and Mean Excess Delay (MED) under IEEE802.15.4a standard is modeled as standard distribution. |
| 24113 | 再以信道瞬时分布与标准分布间的 KL 散度为检验统计量做似然比检验(Likelihood Ratio Test, LRT)来鉴别信道状态。 | Channel state is identified by Likelihood Ratio Test (LRT) based on KL divergence between channel instantaneous distribution and standard distribution. |
| 24114 | 同时提出一种基于 LRT 的定位算法：LRT-Chan 算法。该算法能有效利用受 NLOS 污染的测距数据提高定位精度。 | A localization algorithm named LRT-Chan based on LRT is proposed to improve positioning accuracy by effectively utilizing data contaminated by NLOS. |