基于分布式检测融合技术的水声信号检测方法

研究了分布式检测融合系统的最优检测问题.融合系统由融合中心及多部传感器构成.为了使系统性能达到最优,需要对融合中心的融合规则及各部传感器的判决规则进行全局最优化.文中给出了融合系统全局最优化的必要条件,并给出了求解系统全局最优解的数值迭代算法.仿真结果表明,采用该融合算法对分布式水声信号检测系统进行了优化,可有效提高系统的检测性能.     

深度双重注意力的生成与判别联合学习的行人重识别

在行人重识别任务中存在数据集标注难度大,样本量少,特征提取后细节特征缺失等问题。针对以上问题提出深度双重注意力的生成与判别联合学习的行人重识别。首先,构建联合学习框架,将判别模块嵌入生成模块,实现图像生成和判别端到端的训练,及时将生成图像反馈给判别模块,同时优化生成模块与判别模块。其次,通过相邻的通道注意力模块间连接和相邻空间注意力模块间连接,融合所有通道特征和空间特征,构建深度双重注意力模块,将其嵌入教师模型,使模型能更好地提取行人细节身份特征,提高模型识别能力。实验结果表明,该算法在Market-1501和DukeMTMC-ReID数据集上具有较好的鲁棒性、判别性。     

Optimal and self‐tuning weighted measurement fusion Kalman filters and their asymptotic global optimality

For the multisensor linear discrete time‐invariant stochastic systems with unknown noise variances, using the correlation method, the information fusion noise variance estimators with consistency are given by taking the average of the local noise variance estimators. Substituting them into two optimal weighted measurement fusion steady‐state Kalman filters, two new self‐tuning weighted measurement fusion Kalman filters with a self‐tuning Riccati equation are presented. By the dynamic variance error system analysis (DVESA) method, it is rigorously proved that the self‐tuning Riccati equation converges to the steady‐state optimal Riccati equation. Further, by the dynamic error system analysis (DESA) method, it is proved that the steady‐state optimal and self‐tuning Kalman fusers converge to the global optimal centralized Kalman fuser, so that they have the asymptotic global optimality. Compared with the centralized Kalman fuser, they can significantly reduce the computational burden. A simulation example for the target tracking systems shows their effectiveness. Copyright © 2010 John Wiley & Sons, Ltd.     

Choice of a pertinent color space for color texture characterization using parametric spectral analysis

This article presents a comparison of different color spaces including RGB, IHLS and L?a*b* for color texture characterization. This comparison is based on the fusion of the independent spatial structure and color feature cues. In IHLS and L*a*b*, two channel complex color images are created from the luminance and the chrominance values. For such images, two dimensional complex multichannel linear prediction models are used to perform parametric power spectrum estimation and the structure feature cues are computed from this estimated power spectrum. Quantitative comparison of auto spectra of luminance and combined chrominance channels for different color spaces is done. This comparison is based on the degree of decorrelation between luminance and chrominance information provided by different color space transformations. Three dimensional histograms are used as color feature cues. Then, to classify color textures, Kullback-Leibler divergence based symmetric distance measures are calculated for pure color, luminance structure and chrominance structure feature cues. Individual as well as combined effect of information from all feature cues on classification results is then compared for different color spaces and different color texture data sets. The proposed color texture classification method performs better than the state of the art methods in certain cases. The L*a*b* color space gives us a better characterization of the chrominance spatial structure as well as the overall spatial structure for all of the chosen data sets. Experimental results on pixel classification of color textures are also presented and discussed.     

基于自适应加权融合的标准铜柱鉴选研究

介绍了标准铜柱在塑性测压校准系统的重要作用及其鉴选方法。为提高测压铜柱受压后变形量测量准确性,提出了用自适应加权融合算法应用于变形量的融合计算,利用所提供的数据融合出标准偏差最小的数据融合值,以3.5×8.75、4×6.5、8×13测压铜柱实测数据为例,比较分析了各型号铜柱采用自适应加权融合算法与平均估算法、贝赛尔公式计算法的有效性和融合精度的差异,从理论和实践两个方面验证了该方法的有效性,提高了融合精度。     

Web系统在远程监视系统中的应用

论述通过发掘成熟的Web功能,实现具有专利权SCADA远程监视2011-1-14 14：32：35融合系统。     

多通道信息融合的改进乘积规则

用传统的多通道信息融合乘积计算出的融合分值的动态范围比较小,融合效果不理想,本文在假定所有通道都能同时正常工作的情况下,提出多通道信息融合的改进乘积规则,基本思想是对原乘积规则中的概率密度和融合分值平滑,使得融合分值的动态范围增大,文中的两个实验表明,改进的乘积规则的识别率有明显提高,最后文中给出了在已知每个单一通道系统识别率的条件下,同理想融合方法集成出的系统识别率的上限计算公式。     

激光直接驱动聚变球靶的完全均匀辐照

通过分析球形靶面辐照不均匀度的球谐模,提出了用有限束光实现球靶完全均匀辐照的一般条件,为优化设计多光束辐照系统和评估球靶的辐照不均匀度提供了依据。文中还例举了能实现靶面完全均匀辐照的多光束系统。     

一种快速全局优化的神经网络及其在数据融合中的应用

本文将遗传算法的全局性和EM算法的快速性相结合,提出了一种快速全局优化神经网络,并将其应用于数据融合中。理论与实验结果表明该算法在数据融合中具有很强的鲁棒性。     

两级混合多传感器信息融合中的状态估计

在混合式多传感器信息融合系统中,一部分传感器通过处理它们的数据产生局部航迹,另一部分传感器则只提供检测报告,这些航迹和检测报告被传送到融合中心完成航迹融合和组合滤波。本文提出适合于两级混合式多传感器系统的全局最优状态估计解。在这种结构中,融合中心首先需要融合来自L个传感器的局部估计,然后基于其它N-L个传感器的观测,利用Kalman滤波技术依次更新已融合的航迹。本文还考虑了各传感器分布在不同地理位置时的状态估计问题。