ID 原文 译文
1643 最后，通过触发器的状态提取出测量结果并和无故障 TSV 参考值进行比较。 finally, the measurement results are extracted by the state of trigger and compared with the reference value of fault-free TSV.
1644 实验结果表明，本文脉宽缩减测试方法在故障测量范围、面积开销等方面均有明显改善。 The experimental results show that the proposed method performs better than the existing methods in terms of fault coverage, and area overhead.
1645 可信性作为软件的一种复杂的高复合概念，几十年间都未能取得实质性进展和突破。 As a complex high-composite software concept, the trustworthiness research has failed to make substantial progress and breakthroughs during these decades.
1646 本文在对可信性权威定义分析的基础上，论证了这些定义所涉范围彼此矛盾且不相容，进一步说明从本质出发研究软件可信性概念模型的重要性和必然性。 After analyzing the authority definitions of trustworthiness, this paper dem-onstrates that the scope of them is contradictory and incompatible. It further illustrates that the research of software trustwor-thiness conceptual model from its essence is very important and necessary.
1647 “可信”一词源于社会学，所以应该从社会学的信任理论出发来探讨软件可信性的本质。 The term " trustworthiness" originates from soci-ology; so we should discuss the essence of software trustworthiness based on trust-theory of sociology.
1648 本文在上百篇经典社会学信任理论文献上构建出信任体系模型 STM，并与软件的信任体系进行了对比和映射，提出基于社会学信任理论的软件可信性概念模型 STCM。 This paper constructsa trust system model STM based on hundreds of classical sociological literature on trust-theory. After comparing and map-ping with software trust system, the paper proposes a software trustworthiness conceptual model STCM based on trust theory of sociology.
1649 在 STM 和 STCM 的基础上给出软件可信性概念模型的定义系统。 Based on STM and STCM, a complete concept definition system of software trustworthiness is presented.
1650 最后通过度量评估实验验证了模型是可行的、有效的，为软件可信性的发展提供了新的研究方向。 Final-ly, STCM is proved to be feasible and effective by the measurement and evaluation experiment, which provides a new re-search direction for the advancement of software trustworthiness.
1651 经典的非参数谱分析方法使用滑动窗口来捕捉大多数时间序列的频谱特性，然而这种方法不能很好地应用在时间序列的时频谱是时间连续的信号上。 Classical nonparametric spectral analysis uses sliding windows to capture the dynamic nature of most real-world time series, however, this universally accepted approach fails to exploit the temporal continuity in the data.
1652 对于一些其时频谱满足时间连续频率稀疏的非平稳信号，提出了一种利用部分平行交替方向乘子法(Alternating Direction Method of Multipliers，ADMM)求解谱寻求问题用于此类信号的时频分析方法。 For somenon-stationary signals that are smooth in time and sparse in frequency, a method of computing the spectrum pursuit estimate by using partly parallel alternating direction method of multipliers (ADMM)was used to obtain time-frequency analysis ofthis signal.