基于Log-Gabor小波和正交UDP的人脸识别

针对人脸识别中特征提取的小样本问题,对原始的非监督判别映射(UDP)算法进行了改进,提出一种基于Log-Gabor和正交非监督判别映射(Orthogonal UDP)的人脸识别算法——LGOUDP算法.此算法首先采用Log-Gabor小波对图像进行滤波来提取高阶统计信息,然后提出最大化非局部散度和局部散度的权值差和加入...     

多机器人混合编队控制

提出一种将行为控制和反馈控制相互融合的多机器人混合编队控制方法. 采用基于行为的体系结构模型,将动态死区和动力学方程控制共同应用于多机器人编队控制中,从而改善了基于反馈的跟随领航者方法不能快速适应大角度队形变换的问题. 在AmigoBot机器人平台上的实验证明,该方法具备一定的可行性.     

核空间正交及不相关邻域保持鉴别嵌入算法

针对人脸识别中的非线性特征提取问题,基于邻域保持嵌入,提出了一组在核空间具有正交性鉴别矢量和一组在核空间具有统计不相关性鉴别矢量的计算方法.算法首先利用核的方法提取人脸图像中的非线性信息,并将其投影在一个高维非线性空间.然后在目标函数中最小化核空间类内邻域散度并最大化核空间类间邻域散度来增强算法的分类鉴别能力.最后通过...     

Speech-stream detection in short-wave channel based on empirical mode decomposition and higher-order statistics

To capture the presence of speech embedded in nonspeech events and background noise in short-wave non-cooperative communication,an algorithm for speech-stream detection in noisy environments is presented based on Empirical Mode Decomposition (EMD) and statistical properties of higher-order cumulants of speech signals.With the EMD,the noise signals can be decomposed into different numbers of IMFs.Then,the fourth-order cumulant (FOC) can be used to extract the desired feature of statistical properties for IMF components.Since the higher-order cumulants are blind for Gaussian signals,the proposed method is especially effective regarding the problem of speech-stream detection,where the speech signal is distorted by Gaussian noise.With the self-adaptive decomposition by EMD,the proposed method can also work well for non-Gaussian noise.The experiments show that the proposed algorithm can suppress different noise types with different SNRs,and the algorithm is robust in real signal tests.     

多阶段边界参考网络的动作分割

针对现有动作分割算法中过分割问题导致预测错误、造成分割质量下降的现象,提出一种可调视频动作边界信息作为参考的多阶段参考网络,在基于多阶段时间卷积网络的主干网络中,为每个阶段独立引入视频动作边界信息作为参考.各阶段使用相同的边界信息会使模型固化,为使主干网络能够调整参与各阶段输出计算的边界值,对不同样本区分处理,提出多层...     

考虑故障相关的软件可靠性增长模型研究

软件可靠性增长模型是用来评估和预测软件可靠性的重要工具.目前,绝大多数的软件可靠性增长模型并没有考虑故障之间的相关性,也没有考虑测试环境和运行环境的区别.文中提出了一种随机过程类非齐次泊松过程(NHPP)中的考虑故障相关性、测试环境和运行环境差别的模型.在两组失效数据上的实验分析表明:对这两组失效数据,文中提出的模型比其他一些非齐次泊松过程类模型的拟合效果和预测效果更好.     

Design of the multirobot intelligent team formation＇s control architecture and performance analysis of the system

The layered control architecture is designed for the need of the multirobot intelligent team formation. There are three levels：the cooperation task level, the coordination behavior level and the action planning level. The cooperation task level uses the potential grid method, which improves the safety of the path and reduces the calculation complexity. The coordination behavior level uses the reinforcement learning which can strengthen the robots＇ intelligence. The action planning level uses the fuzzy planning methods to realize the action matching. The communication model transfers the message in different level. This architecture shows not only the independence and the intelligence of the single robot but also the cooperation and the coordination among the robots. In each level, the task is distributed reasonably and clearly. Finally the feasibility of the architecture is verified further in the simulation of the experiment. The expansibility of the architecture is good and the architecture can be used in the similar system.     

基于势场栅格法的机器人全局路径规划

综合势场法和栅格法的优点，提出了一个新的全局路径规划方法——势场栅格法、算法在避免局部最优点和降低计算量方面，有着良好的效果；并且可以自动确定栅格粒度．最后，文章分析了影响算法精度的因素，仿真试验表明此算法有良好的可行性和有效性．     

基于遗传蚁群算法的机器人全局路径规划研究

蚁群算法是基于生物界群体启发行为的一种随机搜索寻优方法,它的正反馈性和协同性使其可用于分布式系统,隐含的并行性更使其具有极强的发展潜力,它在解决组合优化问题上有着良好的适应性。因此将其应用到智能机器人全局路径规划中,其目的是探索一种新的路径寻优算法.在基于栅格划分的环境中,研究了机器人路径规划问题中蚁群系统的"外激素"表示及更新方式,并将遗传算法的交叉操作结合到蚁群系统的路径寻优过程中,提高了蚁群系统的路径寻优能力,为蚁群算法的应用提供了一种新的探索.