Open AccessVariable step‐size distributed incremental normalised LMS algorithm
Author(s) -
Shi Long,
Zhao Haiquan
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2015.3882
Subject(s) - convergence (economics) , rate of convergence , node (physics) , algorithm , variable (mathematics) , steady state (chemistry) , least mean squares filter , computer science , mathematics , control theory (sociology) , adaptive filter , engineering , telecommunications , artificial intelligence , mathematical analysis , channel (broadcasting) , chemistry , control (management) , structural engineering , economics , economic growth
A variable step‐size distributed incremental normalised least mean square (DINLMS) algorithm is proposed, in which the time‐varying step‐size of each node in the distributed network is obtained by minimising a posterior estimation error at that node. It overcomes the drawback that fast convergence rate with high steady‐state misalignment or low steady‐state misalignment with slow convergence rate, which always exists in the traditional DINLMS. The simulation results show that the proposed algorithm could achieve a better performance.