| ID | 原文 | 译文 |
| 2783 | 最后进行双直方图均衡得到增强图像。 | Finally, the BHE procedure outputs the final contrast enhanced image. |
| 2784 | 本文选取多个图像数据库进行测试，并与 BBHE(Brightness preserving Bi-Histo-gram Equalization)、BPCLBHE(Brightness Preserving and Contrast Limited Bi-Histogram Equalization)、ESIHE(Exposurebased Sub Image Histogram Equalization)和 DRSHE(Dynamic Range Separate Histogram Equalization)进行比较，同时将信息熵、对比度和 NIQE(Natural Image Quality Evaluator)作为客观评价指标。 | Multiple image databases are selected for testingand compared with BBHE (Brightness preserving Bi-Histogram Equalization), BPCLBHE (Brightness Preserving and Con-trast Limited Bi-Histogram Equalization), ESIHE (Exposure based Sub Image Histogram Equalization)and DRSHE (Dy-namic Range Separate Histogram Equalization), and we use the entropy, contrast and NIQE (Natural Image Quality Evalua-tor)as objective evaluation indexes. |
| 2785 | 实验结果证明，本文算法对各类图像均具有较好的主观视觉效果和客观评价指标，在保留细节的同时兼顾了对比度的增强。 | The experimental results demonstrate that the proposed algorithm outperforms otherstate-of-the-art BHE algorithms on almost all types of images, with better subjective visual effective and better objective score of quality evaluation, and it takes the enhancement of contrast into account while preserving details. |
| 2786 | 针对宽带子阵域自适应波束形成器在实际使用中稳健性下降、对弱信号的检测能力受信噪比限制的问题，提出了一种宽带子阵域特征空间稳健对角减载自适应波束形成方法。 | The robustness of broadband adaptive beamformer decreases in practice and the detection ability of weaksignal is limited by signal noise ratio (SNR). To solve those problems, a broadband robust diagonal reducing adaptive beam-forming based on subarray subspace is proposed. |
| 2787 | 首先提出利用子阵域特征空间投影法修正导引向量并得到球形不确定集的估计，再利用 RCB(Robust Capon Beamformer)算法得到约束条件下的最优权值。 | Firstly, the subarray subspace projection method is used to correct signalsteering vector, and a spherical uncertainty set is designed to get subarray robust capon beamformer (RCB)weight vector. |
| 2788 | 另一方面，利用子阵域互谱密度矩阵的最小特征值作为子阵域非相关噪声功率的估计并进行对角减载，以最优权值对减载矩阵波束形成得到子带波束输出，对每个窄子带重复上述处理，再将结果非相干叠加即可得到本文方法的最终结果。 | On the other hand, the least eigenvalue of subarray cross spectral density matrix is proposed as the estimation of non-correla-ted noise power, and the main diagonal of subarray cross spectral density matrix is subtracted from the noise power and pro-cessed by the proposed beamformer. The above process is repeated for each sub-band and all outputs are incoherentlysummed to obtain the final result of the proposed method. |
| 2789 | 理论及实验分析表明方法能提高自适应波束形成器的稳健性及输出信噪比。 | Theoretical and experimental analysis shows that the proposed al-gorithm can improve the robustness and the output SNR of the adaptive beamformer. |
| 2790 | 针对变频正弦混沌神经网络寻优精度与收敛速度无法兼顾的问题，通过分析暂态混沌神经网络的优化机制和现有的退火策略，提出了一种基于自适应模拟退火策略的变频正弦混沌神经网络模型。 | The frequency conversion sinusoidal chaotic neural network (FCSCNN)cannot consider search accuracy and convergence speed simultaneously. In order to solve the mentioned problem, a novel self-adaptive simulated annealing (SSA)strategy is proposed by analyzing the optimization mechanism of the transiently chaotic neural network (TCNN)and the exist-ing annealing strategy. |
| 2791 | 该模型可以根据混沌神经元的 Lyapunov 指数来确定合适的自反馈连接权值。 | It can give appropriate self-feedback connection weights based on the characteristics of Lyapunov expo-nent. |
| 2792 | 给出了混沌神经元的倒分岔图、Lyapunov 指数及不同退火函数的时间演化图，证明了自适应模拟退火策略能够自主选择合适的退火速度，更有效的利用混沌全局搜索能力，并加快非混沌态的演化时间。 | The reversed bifurcation, Lyapunov exponent and annealing function evolution diagram of the chaotic neuron are given and the dynamic characteristic is analyzed. It shows that the SSA strategy can choose appropriate annealing speed in different stages, which can not only make full use of chaotic global searching ability but also accelerate convergence speed. |