ID 原文 译文
25715 同时，文中也提出了基于该可逆有限状态机电路的可逆时序电路综合方法，并用实例进行了验证。 Furthermore, a synthesis method of reversible sequential circuits based on the proposed reversible FSM is presented and verified by an example．
25716 相比于基于行为重构的可逆有限状态机的综合方法，本文提出的综合方法可以避免原始状态机的逆状态机的求解和增加额外的信号位，从而使得综合过程变得更加简单。 Compared with the synthesis methods of reversible finite state machine based on behavior reconstruction, the proposed synthesis method in this paper can avoid the solution of the inverse state machine of the original state machine and adding extra bits, which makes the synthesis process simpler．
25717 针对船舶机械未知时变谐波噪声的主动控制问题，基于正交锁相环原理，提出了一种归一化 QPLL(Quadrature Phase Locked Loop)的未知时变谐波噪声主动控制方法。 In order to tackle the problem of active control of unknown and time-varying harmonic noise induced byship on-board machinery, a modified normalized QPLL (Quadrature Phase Locked Loop) based active control algorithm is proposed inspired by quadrature phase locked loop tracking mechanism．
25718 通过在相位/频率更新结构中引入参数调整因子，形成一种改进的 QPLL 结构; With the introduction of adjustment parameter inphase/frequency structure, an improved QPLL structure is derived．
25719 引入次级通道，设计并提出了基于 QPLL 的未知时变谐波噪声控制算法。 Then, design of active control algorithm based on QPLLis proposed by introducing secondary path in the control loop．
25720 首先，通过平均化理论和线性化方法，分析该算法的稳定性，指出了次级通道特性和谐波信号幅值对该算法收敛性能的影响; In the proposed algorithm, firstly, performance effect causedby secondary path and amplitude of sinusoidal signal is pointed out by using averaging theory and approximating analysis．
25721 其次，基于分析结果，引入次级通道、幅值归一化措施，形成一种归一化的未知时变谐波噪声主动控制算法，提升稳定性能和收敛速度; Secondly, an improved active control algorithm for time-varying sinusoidal is proposed with the normalization of secondary path and amplitude．
25722 最后，通过仿真验证了归一化改进措施对未知时变谐波噪声主动控制算法综合性能的改善效果。 Finally, simulation results validate the effective performance improvement of active control algorithm for unknown and time-varying harmonic noise．
25723 随着网络规模的不断增大以及网络复杂度的不断提高，传统路由算法面对网络流量在时空分布上的剧烈波动难以兼顾计算复杂度和算法效率。 With the expansion of network scale and network complexity, traditional routing algorithms cannot ensure both the calculation complexity and performance under the large fluctuation of spatial-temporal distribution of network traffic．
25724 近年来，随着软件定义网络和人工智能技术的兴起，基于机器学习的自动路由策略生成逐渐受到关注。 In recent years, with the development of Software-Defined Networking (SDN) and Artificial Intelligence (AI), AI-based methods of automatic routing strategies are gaining attention．