ID 原文 译文
20185 同时为了减少算法的计算量，在算法的实现过程中，先估计出各用户的扩频码，再对观测数据进行处理，从而修正原有的迭代步骤，提出一种修正的SMC算法。 During the realization of the algorithm, in order to reduce the computational complexity, the modified algorithm estimates the spreading code of each user firstly, then processes the observation data, thereby modifies the original iteration step.
20186 仿真结果验证了算法对多种情况的适应性，且在时变的多径信道环境下也能获得较好的估计性能。 Simulation results verify the adaptability of the proposed algorithms for multiple conditions. Moreover, it can obtain good estimation performance in time varying multipath channels.
20187 为提高无线网络入侵检测模型的综合性能，该文将循环神经网络(RNN)算法用于构建无线网络入侵检测分类模型。 In order to improve the comprehensive performance of the wireless network intrusion detection model, Recurrent Neural Network (RNN) algorithm is used to build a wireless network intrusion detection classification model.
20188 针对无线网络入侵检测训练数据样本分布不均衡导致分类模型出现过拟合的问题，在对原始数据进行清洗、转换、特征选择等预处理基础上，提出基于窗口的实例选择算法精简训练数据集。 For the over-fitting problem of the classification model caused by the imbalance of training data samples distribution in wireless network intrusion detection, based on the pre-treatment of raw data cleaning, transformation, feature selection, etc., an instance selection algorithm based on window is proposed to refine the train data-set.
20189 对攻击分类模型的网络结构、激活函数和可复用性进行综合优化实验，得到最终优化模型，分类准确率达到98.6699%，综合优化后的运行时间为9.13 s。 The network structure, activation function and re-usability of the attack classification model are optimized experimentally, so the optimization model is obtained finally. The classification accuracy ofthe optimization model is 98.6699%, and the running time after the model reuse optimization is 9.13 s.
20190 与其他机器学习算法结果比较，该优化方法在分类准确率和执行效率两个方面取得了很好的效果，综合性能优于传统的入侵检测分类模型。 Compared to other machine learning algorithms, the proposed approach achieves good results in classification accuracy and execution efficiency. The comprehensive performances of the proposed model are better than thoseof traditional intrusion detection model.
20191 配置时间过长是制约可重构系统整体性能提升的重要因素，而合理的任务调度技术可有效降低系统配置时间。 Long configuration time is a significant factor which restricts the performance improvement of the reconfigurable system, and a reasonable task scheduling technology can effectively reduce the system configuration time.
20192 该文针对粗粒度动态可重构系统(CGDRS)和具有数据依赖关系的流应用，提出了一种3维任务调度模型。 A three-dimensional task scheduling model for Coarse-Grain Dynamic ReconfigurableSystem (CGDRS) and flow applications with data dependencies is proposed.
20193 首先基于该模型，设计了一种基于预配置策略的任务调度算法(CPSA)； Firstly, based on this model, a Configuration Prefetching Schedule Algorithm (CPSA) applying pre-configured strategy is designed.
20194 然后根据任务间的配置重用性，提出了间隔配置重用与连续配置重用策略，并据此对CPSA算法进行改进。 Then, the interval and continuous configuration reuse strategy are proposed according to the configuration reusability between tasks, and the CPSA algorithm is improved accordingly.