广义正交码索引调制系统的性能分析

摘 要：为了提高码索引调制（code index modulation，CIM）系统的传输效率，提出了一种具有更低复杂度的单输入单输出（single input single output，SISO）的广义正交码索引调制（generalized orthogonal code index modulation，GQCIM）系统。CIM 系统使用扩频码和星座符号传输信息，但只能激活两个扩频码索引和一个调制符号。而 GQCIM 系统以一种新颖的方式克服了只激活一个调制符号的限制，同时充分利用了调制符号的正交性，增加扩频码索引以传输更多的额外信息位，提高了系统的传输效率。此外，分析了GQCIM系统的理论性能，推导了误码率性能的上界。通过蒙特卡罗仿真验证了GQCIM系统的性能，对比发现GQCIM系统的理论和仿真性能一致。而且在相同的传输效率下，结果显示GQCIM系统的性能优于同样具有正交性的调制系统，如广义码索引调制（generalized code index modulation，GCIM）系统、CIM系统、码索引调制-正交空间调制（code index modulation aided quadrature spatial modulation，CIM-QSM）系统、码索引调制-正交空间调制（code index modulation aided spatial modulation，CIM-SM）系统、脉冲索引调制（pulse index modulation，PIM）系统。     

以任意高维纠缠态为量子信道的受控隐形传态

目的是利用高维量子纠缠态为量子信道，讨论未知单粒子态的受控隐形传输问题。以三维量子纠缠态为信道，提出一个二维任意单粒子态的受控隐形传输协议。提出了以任意[d]-维量子纠缠态为量子信道，[t]-维任意单粒子态的隐形传输协议[(t相似文献   

Real‐time thermal states monitoring of absorber tube for parabolic trough solar collector with non‐uniform solar flux

With the world energy shortage problem becoming increasingly prominent, more and more attentions have been paid to the development of renewable energies. Among these sources, solar energy has received extensive attention with its excellent characteristics. The thermal state affects the safety of the solar heat collection system. In this paper, real‐time monitoring of the input heat flux on the inside wall and the temperature field simultaneously of an absorber tube for parabolic trough solar collector were studied. Based on the measured temperatures on the outside wall, the fuzzy adaptive Kalman filter coupled with weighted recursive least squares algorithm (WRLSA) was employed to monitor the heat states of the absorber tube inversely, in which WRLSA was used to acquire the heat flux while fuzzy adaptive Kalman filter was adopted to monitor the temperature field. The method showed strong robustness to resist the ill‐posedness. Accurate monitoring results also can be acquired when there are random disturbances of the heat transfer condition on the inner wall.     

Propagation and termination of an internal crack in continuously cast austenitic stainless steel analyzed by ∑ values and the Schmid factor

The formation mechanism of an internal crack was clarified from the viewpoint of the crystallography and thermal expansion. An inverse pole figure map obtained by EBSD pattern showed that the crack propagated along the grain boundaries having high ∑ values within the columnar zone. After the crack initiation, these positions were considered to undergo cracking followed by propagation toward the equiaxed side. Near the termination position, the grains ahead of crack propagation had a Schmid factor higher than 0.45 consuming elastic strain energy. Thermal expansion measurements showed that the grain with (0 0 1) orientation had the largest expansion while that with (0 1 1) the smallest. The grain boundaries neighboring the combination of (0 0 1) and (0 1 1) grains had the largest thermal stress. Therefore, thermal stress contributed to the initiation of cracking. It was thus proposed to enlarge the equiaxed zone to prevent cracking by discontinuing the crack propagation.     

小尺度交通信号灯的检测与状态识别

交通信号灯识别包括检测和状态识别，在智能交通系统中发挥重要作用。基于YOLOv3算法提出了一种交通信号灯检测与状态识别模型。针对交通信号灯相较于交通场景中其他目标具有尺度小的特性进行了算法的设计：降低骨干网络的下采样倍率以增加小尺度目标的特征描述能力；通过增大特征图的尺度来改进多尺度特征融合；引入广义交并比作为检测任务的损失函数来改进目标边界框的回归效果。同时，根据交通信号灯本身的特性，使用颜色和形状约束的方法对信号灯进行状态识别和类别验证。最后在公开的Bosch交通信号灯数据集上和实际的城区道路进行了实验验证。实验结果表明，所提出的算法能够提升交通信号灯识别的精度和召回率，识别准确率可以达到90%左右。     

Inverse reinforcement learning-based time-dependent A* planner for human-aware robot navigation with local vision

In an environment where robots coexist with humans, mobile robots should be human-aware and comply with humans' behavioural norms so as to not disturb humans' personal space and activities. In this work, we propose an inverse reinforcement learning-based time-dependent A* planner for human-aware robot navigation with local vision. In this method, the planning process of time-dependent A* is regarded as a Markov decision process and the cost function of the time-dependent A* is learned using the inverse reinforcement learning via capturing humans' demonstration trajectories. With this method, a robot can plan a path that complies with humans' behaviour patterns and the robot's kinematics. When constructing feature vectors of the cost function, considering the local vision characteristics, we propose a visual coverage feature for enabling robots to learn from how humans move in a limited visual field. The effectiveness of the proposed method has been validated by experiments in real-world scenarios: using this approach robots can effectively mimic human motion patterns when avoiding pedestrians; furthermore, in a limited visual field, robots can learn to choose a path that enables them to have the larger visual coverage which shows a better navigation performance.     

A new linearly constrained minimum variance beamformer for reconstructing EEG sparse sources

Brain source imaging based on EEG aims to reconstruct the neural activities producing the scalp potentials. This includes solving the forward and inverse problems. The aim of the inverse problem is to estimate the activity of the brain sources based on the measured data and leadfield matrix computed in the forward step. Spatial filtering, also known as beamforming, is an inverse method that reconstructs the time course of the source at a particular location by weighting and linearly combining the sensor data. In this paper, we considered a temporal assumption related to the time course of the source, namely sparsity, in the Linearly Constrained Minimum Variance (LCMV) beamformer. This assumption sounds reasonable since not all brain sources are active all the time such as epileptic spikes and also some experimental protocols such as electrical stimulations of a peripheral nerve can be sparse in time. Developing the sparse beamformer is done by incorporating L1-norm regularization of the beamformer output in the relevant cost function while obtaining the filter weights. We called this new beamformer SParse LCMV (SP-LCMV). We compared the performance of the SP-LCMV with that of LCMV for both superficial and deep sources with different amplitudes using synthetic EEG signals. Also, we compared them in localization and reconstruction of sources underlying electric median nerve stimulation. Results show that the proposed sparse beamformer can enhance reconstruction of sparse sources especially in the case of sources with high amplitude spikes.     

基于双树复小波的无参考立体图像质量评价

随着3D技术的不断发展，立体图像的使用领域越来越广泛，同时人们对图像的清晰度要求越来越高，因此，立体图像的质量评价成为关注点，基于此，提出了一种基于双树复小波变换的立体图像质量评价算法。使用双树复小波变换对立体图像的左、右视图进行处理，生成纹理结构图像，且根据最小能量误差的原理，获取左右视图的视差图；对纹理结构图像和视差图提取非对称广义高斯分布模型的参数、梯度幅值、相对梯度方向方差和奇异值曲线与坐标轴的面积等特征；使用AdaBoosting BP神经网络，进行训练和预测立体图像的质量得分。在LIVE立体图像数据库上的实验结果表明，新方法预测得分与主观得分有较好的一致性，获得了比较好的实验结果。     

发酵乳杆菌HCS08-005耐逆性及对体外细胞免疫调节作用的研究

目的 研究发酵乳杆菌(Lactobacillus fermentum) HCS08-005耐逆性及对体外细胞的免疫调节作用。方法 考察发酵乳杆菌HCS08-005的耐酸耐胆盐能力，并应用发酵乳杆菌HCS08-005细胞裂解物，处理小鼠单核巨噬细胞RAW264.7和小鼠脾脏细胞，用酶联免疫吸附测定试剂盒检测各类炎症因子包括肿瘤坏死因子-α (tumor necrosis factor-α，TNF-α)、白细胞介素-2 (inter-leukin-2，IL-2)、白细胞介素-12 (inter-leukin-12，IL-12)、γ干扰素(interferon-γ，IFN-γ)的表达水平。结果 显示发酵乳杆菌HCS08-005有较好的耐逆性，能够耐受酸和胆盐环境到达肠道发挥作用。不同浓度的发酵乳杆菌HCS08-005细胞裂解物对小鼠脾脏细胞和巨噬细胞分泌炎症因子均有极显著影响(P<0.01)，在质量浓度为100 μg/g时，IL-2分泌量为421.49 pg/g，TNF-α分泌量为161.23 pg/g，IFN-γ分泌量为846.14 pg/g，IL-12分泌量为12.88 pg/g，因子水平极显著提高(P<0.01)。结论 在体外细胞试验中，发酵乳杆菌HCS08-005有较好的耐逆性，对体外细胞有免疫调节作用。