ID 原文 译文
19825 针对基于非正交多址接入(NOMA)技术的中继通信系统，在兼顾系统性能与计算复杂度的基础上，该文提出一种结合统计信道信息(S-CSI)和瞬时信道信息(I-CSI)的混合功率分配策略(H-PAS)来有效实现上述折中。 A novel scheme termed Hybrid Power Allocation Strategy (H-PAS), which is integrated with Statistical Channel State Information (S-CSI) and Instantaneous Channel State Information (I-CSI), is proposed for Non-Orthogonal Multiple Access (NOMA) based on cooperative relaying systems to achieve a better performance-complexity tradeoff.
19826 仿真结果表明，NOMA方案在H-PAS策略下，一方面比单纯利用S-CSI时的传统正交多址接入技术具有更高的频谱效率； Simulation results demonstrate that, with the proposed H-PAS, on the one hand, NOMA shows distinct advantage on the sum-rate compared with conventional orthogonal multiple access techniques in which only the knowledge of S-CSI is available;
19827 另一方面在和速率差别不大的情况下，又比单纯利用I-CSI时的NOMA方案具有更低的信令开销和计算复杂度。 On the other hand, NOMA reduces the signaling overhead and computational complexity at the expense of marginal sum rate degradation when compared with the cases in which only the knowledge of I-CSI is available for it.
19828 针对常规最大类间方差法在多阈值图像分割中存在的运算量大、计算时间长、分割精度较低等问题，该文提出一种基于改进的自适应差分演化(JADE)算法的2维Otsu多阈值分割法。 The multi-threshold image segmentation of the classical 2D maximal between-cluster variance method has deficiencies such as large computation, long calculation time, low segmentation precision and so on. Amulti-threshold segmentation of 2D Otsu based on improved Adaptive Differential Evolution (JADE) algorithm is proposed.
19829 首先，为增强初始化种群的质量、提升控制参数的适应性，将混沌映射机制融入到JADE算法中； Firstly, in order to enhance the quality of the initialized population and improve the adaptabilityof the control parameters, the chaotic mapping mechanism is integrated into the JADE algorithm.
19830 进而，通过该改进算法求解2维 Otsu 多阈值图像的最佳分割阈值； Furthermore, the optimal segmentation threshold of 2D Otsu multi-threshold image is solved by improvedJADE algorithm.
19831 最终，将该算法与差分进化(DE), JADE，改进正弦参数自适应的差分进化(LSHADE-cnEpSin)以及增强的适应性微分变换差分进化(EFADE) 4种算法的2维Otsu多阈值图像分割进行比较。 Finally, the algorithm is compared with multi-threshold image segmentation method of 2DOtsu based on Differential Evolution (DE), JADE, Improved Differential Evolution with Adaptive Sinusoidal Parameters (LSHADE-cnEpSin) and Enhanced Adaptive Differential Transformation Differential Evolution(EFADE) algorithm.
19832 实验结果表明，与其它4种算法相比，基于改进JADE算法的2维Otsu多阈值图像分割在分割速度以及精度上均有较明显的改善。 The experimental results show that compared with the other four algorithms, the multi-threshold image segmentation of 2D Otsu based on the improved JADE algorithm has a significant improvement in terms of segmentation speed and accuracy.
19833 针对如何提高纸币识别率的问题，该文提出一种改进深度卷积神经网络(DCNN)的纸币识别算法。 In order to improve the recognition rate of banknotes, the improved banknote recognition algorithm based on Deep Convolutional Neural Network(DCNN) is proposed.
19834 该算法首先通过融合迁移学习、带泄露整流(Leaky ReLU)函数、批量归一化(BN)和多层次残差单元构造深度卷积层，对输入的不同尺寸纸币进行稳定而快速的特征提取与学习； Firstly, the algorithm constructs a deepconvolution layer by integrating transfer learning, Leaky-Rectified Liner Unit (Leaky ReLU) function, BatchNormalization(BN) and multi-level residual unit that perform stable and fast feature extraction and learning oninput different size banknotes.