基于自适应网络的分布式参数估计近年来受到了日益广泛的关注。现有的分布式参数估计算法尽管在无攻击的安全网络中表现良好,但在遭受如虚假数据注入(false data injection, FDI)攻击的对抗网络中,由攻击者注入的虚假数据(也称恶意数据...基于自适应网络的分布式参数估计近年来受到了日益广泛的关注。现有的分布式参数估计算法尽管在无攻击的安全网络中表现良好,但在遭受如虚假数据注入(false data injection, FDI)攻击的对抗网络中,由攻击者注入的虚假数据(也称恶意数据)会随着节点间的通信和协作在网络中扩散,导致算法估计性能的恶化。若算法不能从攻击中快速恢复估计性能(即算法对攻击不具有弹性),则可能导致严重的后果。为此,简要介绍了弹性分布式参数估计算法所解决的基本问题及基本算法原理;从FDI攻击检测和弹性参数估计策略2个方面,系统地总结了近年来弹性分布式参数估计算法的研究进展,并分析了其在遭受FDI攻击的对抗网络中的性能;最后,探讨了现有弹性分布式参数估计算法的发展趋势和未来潜在的研究方向。展开更多
In this study,it is proposed that the diffusion least mean square(LMS)algorithm can be improved by applying the fractional order signal processing methodologies.Application of Caputo’s fractional derivatives are cons...In this study,it is proposed that the diffusion least mean square(LMS)algorithm can be improved by applying the fractional order signal processing methodologies.Application of Caputo’s fractional derivatives are considered in the optimization of cost function.It is suggested to derive a fractional order variant of the diffusion LMS algorithm.The applicability is tested for the estimation of channel parameters in a distributed environment consisting of randomly distributed sensors communicating through wireless medium.The topology of the network is selected such that a smaller number of nodes are informed.In the network,a random sleep strategy is followed to conserve the transmission power at the nodes.The proposed fractional ordermodified diffusionLMS algorithms are applied in the two configurations of combine-then-adapt and adapt-then-combine.The average squared error performance of the proposed algorithms along with its traditional counterparts are evaluated for the estimation of the Rayleigh channel parameters.Amathematical proof of convergence is provided showing that the addition of the nonlinear term resulting from fractional derivatives helps adjusts the autocorrelation matrix in such a way that the spread of its eigenvalues decreases.This increases the convergence as well as the steady state response even for the larger step sizes.Experimental results are shown for different number of nodes and fractional orders.The simulation results establish that the accuracy of the proposed scheme is far better than its classical counterparts,therefore,helps better solves the channel gains estimation problem in a distributed wireless environment.The algorithm has the potential to be applied in other applications related to learning and adaptation.展开更多
This work is devoted to the discussion of stochastic reaction diffusion equations and some new theorems on Lagrange stability in mean square of the solution are established via Lyapunov method which is nothing to be d...This work is devoted to the discussion of stochastic reaction diffusion equations and some new theorems on Lagrange stability in mean square of the solution are established via Lyapunov method which is nothing to be done in the past.展开更多
使用近红外光谱仪获取由高岭土、白云母和蒙脱石三种岩石矿物粉末混合成的模拟天然岩石样本的近红外漫反射光谱信息,通过标准归一化(standard normal variable)的方法对光谱数据进行预处理,采用随机森林(random forest)进行数学建模,对...使用近红外光谱仪获取由高岭土、白云母和蒙脱石三种岩石矿物粉末混合成的模拟天然岩石样本的近红外漫反射光谱信息,通过标准归一化(standard normal variable)的方法对光谱数据进行预处理,采用随机森林(random forest)进行数学建模,对岩石样本的组成成分进行预测,预测得到三种岩石成分最小均方根误差分别为:0.088 0,0.095 6,0.121 2。实验结果表明应用近红外漫反射光谱来测定天然岩石中各种矿物成分的含量是可行的,为今后岩石成分的快速检测提供了理论依据。展开更多
文摘基于自适应网络的分布式参数估计近年来受到了日益广泛的关注。现有的分布式参数估计算法尽管在无攻击的安全网络中表现良好,但在遭受如虚假数据注入(false data injection, FDI)攻击的对抗网络中,由攻击者注入的虚假数据(也称恶意数据)会随着节点间的通信和协作在网络中扩散,导致算法估计性能的恶化。若算法不能从攻击中快速恢复估计性能(即算法对攻击不具有弹性),则可能导致严重的后果。为此,简要介绍了弹性分布式参数估计算法所解决的基本问题及基本算法原理;从FDI攻击检测和弹性参数估计策略2个方面,系统地总结了近年来弹性分布式参数估计算法的研究进展,并分析了其在遭受FDI攻击的对抗网络中的性能;最后,探讨了现有弹性分布式参数估计算法的发展趋势和未来潜在的研究方向。
文摘In this study,it is proposed that the diffusion least mean square(LMS)algorithm can be improved by applying the fractional order signal processing methodologies.Application of Caputo’s fractional derivatives are considered in the optimization of cost function.It is suggested to derive a fractional order variant of the diffusion LMS algorithm.The applicability is tested for the estimation of channel parameters in a distributed environment consisting of randomly distributed sensors communicating through wireless medium.The topology of the network is selected such that a smaller number of nodes are informed.In the network,a random sleep strategy is followed to conserve the transmission power at the nodes.The proposed fractional ordermodified diffusionLMS algorithms are applied in the two configurations of combine-then-adapt and adapt-then-combine.The average squared error performance of the proposed algorithms along with its traditional counterparts are evaluated for the estimation of the Rayleigh channel parameters.Amathematical proof of convergence is provided showing that the addition of the nonlinear term resulting from fractional derivatives helps adjusts the autocorrelation matrix in such a way that the spread of its eigenvalues decreases.This increases the convergence as well as the steady state response even for the larger step sizes.Experimental results are shown for different number of nodes and fractional orders.The simulation results establish that the accuracy of the proposed scheme is far better than its classical counterparts,therefore,helps better solves the channel gains estimation problem in a distributed wireless environment.The algorithm has the potential to be applied in other applications related to learning and adaptation.
基金Research supported by the National Natural Science Foundation of China (60574042).
文摘This work is devoted to the discussion of stochastic reaction diffusion equations and some new theorems on Lagrange stability in mean square of the solution are established via Lyapunov method which is nothing to be done in the past.
基金supported by National Basic Research Program of China(973 Program,2010CB732400)the National Natural Science Foundation of China(NSFC)(20821063,20873063,51071084,and 21273113)the Natural Science Foundation of Jiangsu Province(BK2010389)
