首页|Distributed Least Squares Algorithm of Continuous-Time Stochastic Regression Model Based on Sampled Data
Distributed Least Squares Algorithm of Continuous-Time Stochastic Regression Model Based on Sampled Data
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
万方数据
维普
In this paper,the authors consider the distributed adaptive identification problem over sensor networks using sampled data,where the dynamics of each sensor is described by a stochastic differential equation.By minimizing a local objective function at sampling time instants,the authors propose an online distributed least squares algorithm based on sampled data.A cooperative non-persistent excitation condition is introduced,under which the convergence results of the proposed algorithm are established by properly choosing the sampling time interval.The upper bound on the accumulative regret of the adaptive predictor can also be provided.Finally,the authors demonstrate the cooperative effect of multiple sensors in the estimation of unknown parameters by computer simulations.
Cooperative excitation conditiondistributed least squaresregretsampled datastochas-tic differential equation
ZHU Xinghua、GAN Die、LIU Zhixin
展开 >
The Key Laboratory of Systems and Control,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,and School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing 100190,China
万方数据
维普
