Link probability control for probabilistic diffusion least-mean squares over resource-constrained networks
Link probability control for probabilistic diffusion least-mean squares over resource-constrained networks
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DOI：
10.1109/icassp.2010.5495952
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发表时间：
2010-03
期刊：
影响因子：
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通讯作者：
Noriyuki Takahashi;I. Yamada
中科院分区：
文献类型：
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作者：
Noriyuki Takahashi;I. Yamada
本文提出了一种有效的链路概率控制策略，用于解决通信资源平均使用受到限制的概率扩散网络上的分布式估计问题。所提出的算法控制链路概率，以便在给定资源约束下最小化估计误差。仿真结果表明，采用所提出的概率控制的概率扩散最小均方（LMS）算法不仅优于静态概率算法，而且还减少了节点间的通信量。
This paper presents an efficient link probability control strategy for distributed estimation problems over probabilistic diffusion networks where the mean usage of communication resources is restricted. The proposed algorithm controls link probabilities so that the estimation error is minimized under given resource constraints. Simulation results show that the probabilistic diffusion least-mean squares (LMS) algorithm with the proposed probability control not only outperforms those with static probabilities but also reduces the amount of communications among nodes.