no code implementations • 10 Oct 2023 • Die Gan, Siyu Xie, Zhixin Liu, Jinhu Lv
In this paper, we consider the distributed filtering problem over sensor networks such that all sensors cooperatively track unknown time-varying parameters by using local information.
no code implementations • 5 Mar 2022 • Die Gan, Zhixin Liu
In this paper, a distributed stochastic gradient (SG) algorithm is proposed where the estimators are aimed to collectively estimate an unknown time-invariant parameter from a set of noisy measurements obtained by distributed sensors.
no code implementations • 5 Mar 2022 • Die Gan, Zhixin Liu
A distributed sparse least squares algorithm is proposed by minimizing a local information criterion formulated as a linear combination of accumulative local estimation error and L_1-regularization term.
no code implementations • 19 Oct 2021 • Die Gan, Zhixin Liu
The simultaneous estimation for both the system orders and parameters brings challenges for the theoretical analysis.