Variable step-size strategy for distributed parameter estimation of compressible systems in WSNs

M. O. B. Saeed, A. Zerguine, M. S. Sohail, S. Rehman, W. Ejaz, A. Anpalagan
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引用次数: 4

Abstract

The Internet of Things (IoT) paradigm depends on sensor networks to collect data and perform information processing as well as communication tasks to attain a common goal. This work presents the formulation and analysis of a sparsity-based variable step-size distributed least-mean-square algorithm based on the diffusion cooperation scheme in wireless sensor networks. In particular, the scheme is applied to compressible systems of which the sparse systems are a special case. The performance of the algorithm is assessed for compressible systems in comparison with existing algorithms in order to showcase the superiority of the proposed algorithm. The proposed scheme is then applied to diffusion-based wireless sensor networks for estimating a compressible system and steady-state analysis is carried out for the proposed scheme.
WSNs中可压缩系统分布参数估计的变步长策略
物联网(IoT)范例依赖于传感器网络来收集数据并执行信息处理以及通信任务以实现共同目标。本文提出了一种基于稀疏度的基于扩散协作方案的可变步长分布最小均方算法。特别地,该格式适用于可压缩系统,其中稀疏系统是一种特殊情况。通过与现有算法的比较,对该算法在可压缩系统中的性能进行了评估,以展示该算法的优越性。然后将所提出的方案应用于基于扩散的无线传感器网络,用于估计可压缩系统,并对所提出的方案进行了稳态分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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