CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Continuous-time multi-agent network for distributed least absolute deviation
Qingshan Liu; Yan Zhao; Long Cheng
2015
Conference Name12th International Symposium on Neural Networks (ISNN)
Conference DateOCT 15-18, 2015
Conference PlaceJeju
CountrySouth Korea
AbstractThis paper presents a continuous-time multi-agent network for distributed least absolute deviation (DLAD). The objective function of the DLAD problem is a sum of many least absolute deviation functions. In the multi-agent network, each agent connects with its neighbors locally and they cooperate to obtain the optimal solutions with consensus. The proposed multi-agent network is in fact a collective system with each agent being considered as a recurrent neural network. Simulation results on a numerical example are presented to illustrate the effectiveness and characteristics of the proposed distributed optimization method.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23138
Collection复杂系统管理与控制国家重点实验室_先进机器人
Recommended Citation
GB/T 7714
Qingshan Liu,Yan Zhao,Long Cheng. Continuous-time multi-agent network for distributed least absolute deviation[C],2015.
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