ID 原文 译文
23655 该文分析偏置温度不稳定性(BTI)，包括负偏置温度不稳定性(NBTI)和正偏置温度不稳定性(PBTI)对软差错率的影响，提出从关键电荷值和延迟两个因素综合考虑。 In this paper, from critical charge and delay points of view, the effects of Bias Temperature Instability (BTI), including Negative BTI (NBTI) and Positive BTI (PBTI), on Soft Error Rate (SER) are analyzed.
23656 首先分析 BTI 效应下两个因素如何变化，推导了延迟受 BTI 影响的变化模型，介绍关键电荷的变化机理。 Firstly, how BTI affects critical charge and delay is focused on. The delay increasing model is derived, and the critical charge changing procedure is introduced.
23657 然后探讨将两个因素结合到软差错率(SER)评估中，推导了融入关键电荷值的 SER 计算模型，提出将延迟的变化导入到电气屏蔽中的方法。 Further, using the derived SER computational model considering critical charge, and mapping the changed delay into electrical mask procedure, the SER is accurately calculated.
23658 基于 ISCAS89 基准电路上的实验验证了综合两种因素考虑 BTI 效应评估 SER 的有效性和准确性。 Experimental results on ISCAS89 benchmark circuits show that, considering two factors of BTI, SER estimation has high accuracy.
23659 经典 MDS-MAP 算法在无线传感器网络定位中存在误差较大及计算量随网络规模增大而急剧增加的缺点。 The classical MDS-MAP algorithm has the disadvantage of large error and the computational complexity increases sharply with the increase of network size in the localization of wireless sensor networks.
23660 该文设计了基于自身和邻居节点剩余能量大小的成簇方法，形成的簇具有适当节点连接度和簇大小，降低了下一步定位算法的计算量和误差。 The clustering method based on the residual energy of the neighbor nodes is designed. The cluster has the proper node degree and cluster size, which reduces the calculation amount and error of the next-step localization algorithm.
23661 然后对于仅有连通信息的簇内节点，利用时间差测距方法获得簇首与其他单跳节点间距离。 Then, for the intra-cluster nodes with only connectivity information, the distance between the sink and other single-hop nodes is obtained using the time difference ranging method.
23662 提出多跳节点间距离误差校正算法，利用相邻节点的几何关系及节点连接度信息，获得簇内多跳间隔节点距离。 A multi-hop distance error correction algorithm is proposed. The distance between nodes in a cluster is obtained using the geometrical relationship of neighboring nodes and the node connectivity.
23663 采用多维标度技术计算各簇内节点相对坐标，融合簇间坐标并通过锚节点转换为绝对坐标，最终实现节点的定位。 Multi-Dimensional Scaling (MDS) is used to calculate the relative coordinates of nodes in each cluster, and the inter-cluster coordinates are merged and converted into absolute coordinates by the anchor nodes. Finally, the localization of the nodes is realized.
23664 所提方法通过能量分簇及多跳间隔节点加权几何距离校正算法，相对于经典多维标度算法定位提供更准确的节点间距离信息，能够在进一步提高定位精度的基础上降低无线传感器网络定位功耗。 The proposed method provides more accurate information of inter-node distance based on energy clustering and multi-hop interval weighted geometric distance correction algorithm. Compared with classical MDS algorithm, this method can further improve the positioning accuracy and reduce the power consumption of wireless sensor network localization.