Distributed Recursive Projection Identification with Binary-Valued Observations  

作　　者：WANG Ying ZHAO Yanlong ZHANG Ji-Feng 

机构地区：[1]Key Laboratory of Systems and Control,Institute of Systems Science,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China [2]School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing 100049,China.

出　　处：《Journal of Systems Science & Complexity》2021年第5期2048-2068,共21页系统科学与复杂性学报（英文版）

基　　金：National Key R&D Program of China under Grant No.2018YFA0703800;the National Natural Science Foundation of China under Grant Nos.61877057 and 62025306;Open Fund Program of Beijing National Research Center for Information Science and Technology。

摘　　要：This paper investigates a distributed recursive projection identification problem with binaryvalued observations built on a sensor network,where each sensor in the sensor network measures partial information of the unknown parameter only,but each sensor is allowed to communicate with its neighbors.A distributed recursive projection algorithm is proposed based on a specific projection operator and a diffusion strategy.The authors establish the upper bound of the accumulated regrets of the adaptive predictor without any requirement of excitation conditions.Moreover,the convergence of the algorithm is given under the bounded cooperative excitation condition,which is more general than the previously imposed independence or persistent excitations on the system regressors and maybe the weakest one under binary observations.A numerical example is supplied to demonstrate the theoretical results and the cooperative effect of the sensors,which shows that the whole network can still fulfill the estimation task through exchanging information between sensors even if any individual sensor cannot.

关 键 词：Adaptive predictor binary-valued observations cooperative excitations distributed parameter estimation 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]