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Steady-State Analysis of Incremental LMS Adaptive Networks With Noisy Links

机译:具有噪声链路的增量LMS自适应网络的稳态分析。

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摘要

Recently proposed adaptive networks assume perfect communication among the nodes. In this correspondence, we extend existing analysis to study the performance of incremental least mean square (LMS) adaptive networks in a more realistic case in which communication links between nodes are considered noisy. More precisely, using weighted spatial-temporal energy conservation relation, we arrive a variance relation which contains moments that represent the effects of noisy links. We evaluate these moments and derive closed-form expressions for the mean-square deviation (MSD), excess mean-square error (EMSE) and mean-square error (MSE) to explain the steady-state performance at each individual node. The derived expressions have good match with simulations. However, the main result is that unlike the ideal link case, the steady-state MSD, EMSE, and MSE curves are not monotonically increasing functions of the step-size parameter when links are noisy. We illustrate this behavior and also find the optimal step-size in a closed-form (for a special case) which minimizes the steady-state values of MSD, EMSE, and MSE in each node. Simulations are also provided to clarify the derived theoretical results.
机译:最近提出的自适应网络假定节点之间的完美通信。在这种对应关系中,我们将现有分析扩展到更现实的情况下,即在节点之间的通信链接被认为是嘈杂的情况下,研究增量最小均方(LMS)自适应网络的性能。更准确地说,使用加权的时空能量守恒关系,我们得出了一个方差关系,其中包含表示噪声链接影响的矩。我们评估这些时刻,并得出均方差(MSD),超额均方误差(EMSE)和均方误差(MSE)的闭式表达式,以解释每个节点的稳态性能。导出的表达式与仿真具有很好的匹配性。但是,主要结果是,与理想的链接情况不同,当链接嘈杂时,稳态MSD,EMSE和MSE曲线不会单调增加步长参数的函数。我们说明了这种行为,并以闭合形式(对于特殊情况)找到了最佳步长,从而使每个节点中的MSD,EMSE和MSE的稳态值最小。还提供了仿真以阐明派生的理论结果。

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