Lee, Donggil Lim, Yoonseob 2025-03-19T14:30:27Z 2025-03-19T14:30:27Z 2025-03-19 2025-02 1598-6446 https://pubs.kist.re.kr/handle/201004/151889 This paper proposes a distributed algorithm for estimating the network size, which refers to the total number of agents in a network. Our approach is based on an optimization problem, where the solution corresponds to the network size and the objective function can be decomposed into individual agents' objectives. This enables the use of distributed methods such as the primal-dual gradient method. We focus on a continuous-time primal-dual gradient method and adapt it using an implicit-explicit scheme to run in discrete time. This approach eliminates the need for small step sizes and ensures rapid convergence. Unlike existing methods that require specific initial values, our method can provide the network size regardless of the initial values, making it robust to network changes. English 제어·로봇·시스템학회 Initialization-free Distributed Network Size Estimation via Implicit-explicit Discretization Method Article 10.1007/s12555-024-0535-7 1 International Journal of Control, Automation, and Systems, v.23, no.2, pp.664 - 673 International Journal of Control, Automation, and Systems 23 2 664 673 N scie scopus kci ART003171815 001415358700013 2-s2.0-85218358323 Automation & Control Systems Automation & Control Systems Article CONVERGENCE CONSENSUS SYSTEMS ADMM Distributed algorithm implicit-explicit discretization network size estimation primal-dual method