ID 原文 译文
20255 与软件仿真验证相比，所提方法可以有效缩短数字电路的功能验证时间； Compared with software simulation verification, the proposed method can effectively shorten thefunctional verification time of digital circuits;
20256 在功能验证效率和验证知识产权可重用方面表现优于现有的FPGA原型验证技术。 it is superior to existing FPGA prototyping technology in termsof functional verification efficiency and verification of intellectual property reusability.
20257 移动边缘计算(MEC)通过在无线网络边缘为用户提供计算能力，来提高用户的体验质量。 Mobile Edge Computing (MEC) improves the quality of users experience by providing users with computing capabilities at the edge of the wireless network.
20258 然而，MEC的计算卸载仍面临着许多问题。 However, computing offloading in MEC still facessome problems.
20259 该文针对超密集组网(UDN)的MEC场景下的计算卸载，考虑系统总能耗，提出卸载决策和资源分配的联合优化问题。 In this paper, a joint optimization problem of offloading decision and resource allocation is proposed for the computation offloading problem in Ultra-Dense Networks (UDN) with MEC.
20260 首先采用坐标下降法制定了卸载决定的优化方案。 To solve this problem, firstly, the coordinate descent method is used to formulate the optimization scheme for the offloading decision.
20261 同时，在满足用户时延约束下采用基于改进的匈牙利算法和贪婪算法来进行子信道分配。 Meanwhile, the improved Hungarian algorithm and greedy algorithm are used to allocate the channelsto meet the user’s delay requirements.
20262 然后，将能耗最小化问题转化为功率最小化问题，并将其转化为一个凸优化问题得到用户最优的发送功率。 Finally, the problem of minimizing energy consumption is converted intoa problem of minimizing power. Then it is converted into a convex optimization problem to get the user’soptimal transmission power.
20263 仿真结果表明，所提出的卸载方案可以在满足用户不同时延的要求下最小化系统能耗，有效地提升了系统性能。 Simulation results show that the proposed scheme can minimize the energy consumption of the system while satisfying the users’ different delay requirements, and improve effectively the performance of the system.
20264 与经典的K均值聚类算法相比，模糊C均值(FCM)聚类算法通过引入模糊因子，考虑不同聚类数据簇之间的相互关系，得到可分性更好的聚类结果。 Comparing with K-means, Fuzzy logic is introduced in Fuzzy C-Means to handle the information between clusters. It can obtain better cluster results.