Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks
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...
Enregistré dans:
Auteurs principaux: | Azam Khalili, Vahid Vahidpour, Amir Rastegarnia, Ali Farzamnia, Kenneth Teo Tze Kin, Saeid Sanei |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/bf739746f80e4649b03e778d174876a0 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Using Histological Staining Techniques to Improve Visualization and Interpretability of Tooth Cementum Annulation Analysis
par: Petrovic,Bojan, et autres
Publié: (2021) -
Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm
par: Yafeng Zhong, et autres
Publié: (2021) -
Crown Formation Times of Deciduous Teeth and Age at Death in Neolithic Newborns
par: Sipovac,Milica, et autres
Publié: (2021) -
Nonparametric Multivariate Density Estimation: Case Study of Cauchy Mixture Model
par: Tomas Ruzgas, et autres
Publié: (2021) -
Rough North Correction Estimation Algorithm Based on Terrain Visibility
par: Ondrej Nemec, et autres
Publié: (2021)