A variable step-size adaptive system identification algorithm based on modified decorrelation principle
- 10.2991/icsmim-15.2016.78How to use a DOI?
- decorrelation; variable step-size LMS algorithm; adaptive system identification; Labview
To overcome the defects of traditional adaptive Least-mean-square(LMS) algorithm, figure out the problem that the existing algorithms’ system identification abilities would decline while their input signals are correlated with each other, a novel variable step-size and variable parameters adaptive system identification algorithm based on modified decorrelation principle is proposed. The design theories and process, the selection principles of the adjusting parameters and the performance analysis of the algorithm are all given below. In the algorithm, the rate of its convergence is improved by the modified decorrelation principle. Variable step size in the algorithm is based on hyperbolic tangent function, it is adjusted by the mean value of the gradient vector, so the system can modify it step size by the energy of the input signals and the real-time error. The variable step size also introduce the self-correlation of the real-time error to retrain the influence of the independent noises. Theory and simulation results verified the system identification abilities and the superiorities of the algorithm under different circumstances.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Huamin Ge AU - Qing Wan AU - Weiwei Zhao PY - 2016/01 DA - 2016/01 TI - A variable step-size adaptive system identification algorithm based on modified decorrelation principle BT - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials PB - Atlantis Press SP - 414 EP - 426 SN - 2352-538X UR - https://doi.org/10.2991/icsmim-15.2016.78 DO - 10.2991/icsmim-15.2016.78 ID - Ge2016/01 ER -