一种新型频域均衡器在水声通信中的应用

在传统频域均衡器的基础上,结合多载波频移键控调制方式的频谱结构,利用接收信号和参考信号的相关性及均衡器的滤波系数,提出了一种兼具均衡与解调功能的新型频域均衡器结构.该均衡器简单、有效地克服了水声信道中多径传播产生的码间干扰和频率选择性衰落等问题,简化了水声通信系统接收机的复杂度. 新型频域均衡器的解调原理以非相关解调算法为基础,但由于利用了均衡器的计算结果,其差错性能优于传统的非相关解调算法,计算机仿真试验表明,改进后的方法使差错性能提高了2 dB;实际水声通信实验表明,该均衡器能够有效地提高水声通信系统的可靠性,具有很好的应用前景.     

环多肽晶体的浮动电荷极化力场模拟

利用原子键电负性均衡结合分子力场方法(ABEEM/MM)对五种环多肽晶体进行了研究. 与传统力场相比, 该方法中的静电势包含了分子内和分子间的静电极化作用, 以及分子内电荷转移影响, 同时加入了化学键等非原子中心电荷位点, 合理地体现了分子中的电荷分布. 相对其他极化力场模型, 具有计算量较小的特点. 该模型下计算得到的环多肽分子单元相对实验测得的结构的原子位置、氢键长度和二面角的均方根偏差分别为0.009 nm、0.013 nm和5.16°, 能够很好地重复实验结果. 总体上, 其结果优于或相当于其他力场模型, 适用于对实际蛋白质体系的模拟和研究.     

Effective contrast enhancement method for color night vision

Image fusion refers to the techniques that integrate complementary information from multiple image sensors’ data in a way that makes the new images more suitable for human visual perception. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Firstly, the contrast of infrared and visible images is enhanced using local histogram equalization and median filter. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To enhance the color contrast between the target and the background, the scaling factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot and cold targets are all popped out with intense colors while the background details present natural color appearance. Target detection experiments through target recognition area, detection rate, target-background discrimination also show that the presented method has a better performance than the former methods.     

水声通信中基于信道辨识的盲turbo均衡方法

水声信道多途效应明显,造成接收信号存在严重的码间干扰(ISI,Intersymbol interference)。基于最小均方误差(MMSE,Minimum mean square error)准则的turbo均衡器级联了均衡和信道译码,能够有效去除ISI,并获得优良的性能。由于水声信道的时变性,传统MMSE-turbo均衡需要周期性的训练序列,以实现连续可靠的通信。训练序列虽然提高了通信的可靠性,但降低了信息的有效传输速率。因此,为提高通信效率,本文提出了一种盲turbo均衡方法,该方法通过引入新的盲信道辨识器来同时获得信道估计响应和已去除部分ISI的初步均衡输出信号,并为turbo均衡提供初始的响应参数和比特软信息。与水声通信中应用较多的盲判决反馈均衡器(DFE,Decision feedback equalizer)相比,海上实验结果证明本文提出的盲turbo均衡方法抗信道多途衰落的能力较强,并且与传统MMSE-turbo均衡相比无需训练序列,因此提高了信息的有效传输速率。     

Site mapping and small molecule blind docking reveal a possible target site on the SARS-CoV-2 main protease dimer interface

The SARS-CoV-2 virus is causing COVID-19 resulting in an ongoing pandemic with serious health, social, and economic implications. Much research is focused in repurposing or identifying new small molecules which may interact with viral or host-cell molecular targets. An important SARS-CoV-2 target is the main protease (M^pro), and the peptidomimetic α-ketoamides represent prototypical experimental inhibitors. The protease is characterised by the dimerization of two monomers each which contains the catalytic dyad defined by Cys¹⁴⁵ and His⁴¹ residues (active site). Dimerization yields the functional homodimer. Here, our aim was to investigate small molecules, including lopinavir and ritonavir, α-ketoamide 13b, and ebselen, for their ability to interact with the M^pro. The sirtuin 1 agonist SRT1720 was also used in our analyses. Blind docking to each monomer individually indicated preferential binding of the ligands in the active site. Site-mapping of the dimeric protease indicated a highly reactive pocket in the dimerization region at the domain III apex. Blind docking consistently indicated a strong preference of ligand binding in domain III, away from the active site. Molecular dynamics simulations indicated that ligands docked both to the active site and in the dimerization region at the apex, formed relatively stable interactions. Overall, our findings do not obviate the superior potency with respect to inhibition of protease activity of covalently-linked inhibitors such as α-ketoamide 13b in the M^pro active site. Nevertheless, along with those from others, our findings highlight the importance of further characterisation of the M^pro active site and any potential allosteric sites.     

基于灰度冗余的红外图像自适应输出窗技术

根据红外图像的特点,提出了一种基于灰度冗余的红外图像自适应输出窗技术.该技术通过对图像灰度直方图的统计,设定适当的阈值,将灰度像素分布为零的灰度级进行完全压缩,将小于阈值的灰度级映射到阈值灰度级,然后将有效灰度级在整个可显示灰度级范围内作等间距排列.该算法在压缩灰度冗余的同时,实现了对有效图像灰度级的无损均衡,提高了图像质量,并能实现实时处理.     

空分复用光纤放大器增益均衡技术研究进展

随着第五代移动通信技术的正式商用,全球网络流量的需求呈爆炸式增长,传统单芯单模光纤通信系统的容量已接近香农极限,实现通信系统的升级扩容迫在眉睫.空分复用光纤通信系统基于空间维度复用,可有效解决未来通信系统的扩容难题,而空分复用光纤放大器是不可或缺的核心器件和研究焦点之一.当多信道功率增益不均衡时,功率差将会随传输距离的...     

语音通信降噪研究

语音通信系统中,语音通过信道传输将不可避免地引入码间串扰和信号畸变,同时受到噪声污染。本文在分析自适应盲均衡算法CMA(constant modulus algorithm）和改进盲均衡算法的基础上,考虑到自适应盲均衡技术在语音噪声控制方面能力有限,将自适应盲均衡技术与小波包掩蔽阈值降噪算法联合使用,形成一种基带语音增强新方法。仿真试验结果显示自适应盲均衡技术可以使星座图变得清晰而紧凑,有效减小误码率。研究证实该方法在语音信号ISI和畸变严重情况下,在白噪及有色噪声不同的噪声环境中都具有稳定的降噪能力,消噪同时可获得汉语普通话良好的听觉效果。     

基于迁移学习的原子力显微镜成像恢复方法

受限于探针针尖结构尺寸,用原子力显微镜进行微纳测量时会产生图像边缘失真.提出了一种基于迁移学习的原子力显微镜成像恢复方法,通过迁移学习训练源模型和靶模型实现一维栅格成像恢复.该方法采用数学形态法中的腐蚀算法生成栅格点云数据,通过U-Net网络源模型从点云中提取针尖卷积效应的特征向量,将权重参数迁移至U-Net网络靶模型,靶模型在自适应正则化方法下进行监督学习.实验结果表明,该方法能有效恢复一维栅格的原子力显微镜测量图像,提高横向分辨力,可用于纳米栅格的线宽检测上.