Network Flows that Solve Least Squares for Linear Equations
It addresses the problem of distributed least-squares computation for linear equations, which is important for networked systems, but the results are incremental as they extend existing continuous-time distributed optimization methods to a specific problem.
This paper proposes a distributed continuous-time algorithm for computing the least-squares solution to linear equations over networks, proving convergence for fixed and switching graphs with various step-size conditions, and establishing exact convergence rates.
This paper presents a first-order {distributed continuous-time algorithm} for computing the least-squares solution to a linear equation over networks. Given the uniqueness of the solution, with nonintegrable and diminishing step size, convergence results are provided for fixed graphs. The exact rate of convergence is also established for various types of step size choices falling into that category. For the case where non-unique solutions exist, convergence to one such solution is proved for constantly connected switching graphs with square integrable step size, and for uniformly jointly connected switching graphs under the boundedness assumption on system states. Validation of the results and illustration of the impact of step size on the convergence speed are made using a few numerical examples.