Distributed Least-Squares over Directed Networks

Mohammad Jahvani, M. Guay
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Abstract

This paper proposes a distributed dynamics that solves the least-squares problem associated with a network system of linear algebraic equations. We consider static directed multi-agent networks. Each agent in the network has access to a private subset of the linear equations. Furthermore, we assume that agents cannot acquire any information about their "out-degrees" at any time. Under the strong connectivity condition on the underlying communication network, we show that the local estimated solution of each agent converges exponentially to the exact least-squares solution of the associated network system of linear algebraic equations.
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有向网络上的分布最小二乘
本文提出了一种求解线性代数方程组网络系统最小二乘问题的分布式动力学方法。我们考虑静态定向多智能体网络。网络中的每个代理都可以访问线性方程的私有子集。此外,我们假设代理在任何时候都无法获得有关其“out-degree”的任何信息。在底层通信网络的强连通性条件下,我们证明了每个智能体的局部估计解指数收敛于相关线性代数方程组的网络系统的精确最小二乘解。
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