TY  - JOUR
AU  - Ramadan, Zayed 
PY  - 2010
TI  - Error Vector Normalized Adaptive Algorithm Applied to Adaptive Noise Canceller and System Identification
JF  - American Journal of Engineering and Applied Sciences
VL  - 3
IS  - 4
DO  - 10.3844/ajeassp.2010.710.717
UR  - https://thescipub.com/abstract/ajeassp.2010.710.717
AB  - Problem statement: This study introduced a variable step-size Least Mean-Square (LMS)
algorithm in which the step-size is dependent on the Euclidian vector norm of the system output error.
The error vector includes the last L values of the error, where L is a parameter to be chosen properly
together with other parameters in the proposed algorithm to achieve a trade-off between speed of
convergence and misadjustment. Approach: The performance of the algorithm was analyzed,
simulated and compared to the Normalized LMS (NLMS) algorithm in several input environments.
Results: Computer simulation results demonstrated substantial improvements in the speed of
convergence of the proposed algorithms over other algorithms in stationary environments for the same
small level of misadjustment. In addition, the proposed algorithm shows superior tracking capability
when the system is subjected to an abrupt disturbance. Conclusion: For nonstationary environments,
the algorithm performs as well NLMS and other variable step-size algorithms.