Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks

Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks

Show other versions (1)

The incremental least-mean-square (ILMS) algorithm is a useful method to perform distributed adaptation and learning in Hamiltonian networks. To implement the ILMS algorithm, each node needs to receive the local estimate of the previous node on the cycle path to update its own local estimate. Howeve...

Full description

Bibliographic Details
Main Authors: Azam Khalili, Vahid Vahidpour, Amir Rastegarnia, Ali Farzamnia, Kenneth Teo Tze Kin, Saeid Sanei
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Sensors
Subjects:
adaptive estimation
coordinate-descent
distributed networks
incremental algorithm
Online Access:https://www.mdpi.com/1424-8220/21/22/7732
Show all versions (2)

Similar Items