State-space fractional-least mean square algorithm

In this work, a novel state-space adaptive algorithm, named state-space fractional-least mean square algorithm (SS-FLMS) is proposed. The proposed algorithm is based on the extension of fractional-least mean square (FLMS) algorithm for dynamic systems. The performance of the proposed algorithm is in...

Full description

Saved in:
Bibliographic Details
Published in2017 First International Conference on Latest trends in Electrical Engineering and Computing Technologies (INTELLECT) pp. 1 - 4
Main Authors Arif, M., Naseem, I., Moinuddin, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2017
Subjects
Adaptive filters
Heuristic algorithms
Kalman filters
mean square error
Power system dynamics
Signal processing algorithms
State estimation
state estimation algorithms
state-space least mean algorithms
Online AccessGet full text

Cover

More Information
Summary:In this work, a novel state-space adaptive algorithm, named state-space fractional-least mean square algorithm (SS-FLMS) is proposed. The proposed algorithm is based on the extension of fractional-least mean square (FLMS) algorithm for dynamic systems. The performance of the proposed algorithm is investigated for the estimation of a highly nonlinear system named Van der Pol oscillator and the outcomes are compared to the conventional state-space least mean square (SSLMS). The proposed algorithm outperforms the standard SSLMS algorithm by achieving fast convergence with lower steady-state. Simulation results are shown to validate the proposed claims.
DOI:10.1109/INTELLECT.2017.8277637