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    Finite-Time Distributed Linear Equation Solver for Minimum l1l_1 Norm Solutions

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    This paper proposes distributed algorithms for multi-agent networks to achieve a solution in finite time to a linear equation Ax=bAx=b where AA has full row rank, and with the minimum l1l_1-norm in the underdetermined case (where AA has more columns than rows). The underlying network is assumed to be undirected and fixed, and an analytical proof is provided for the proposed algorithm to drive all agents' individual states to converge to a common value, viz a solution of Ax=bAx=b, which is the minimum l1l_1-norm solution in the underdetermined case. Numerical simulations are also provided as validation of the proposed algorithms
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