Signed Least Mean Kurtosis-Based Adaptive Line Enhancer
Ji-cheng Ling, HE Long-qing, Yecai Guo · 2006
Based on the aim of the characteristic of error kurtosis and signed-error, a novel algorithm of sign least mean kurtosis based adaptive line enhancer (SLMKBALE) is proposed. Simulation results have shown that the computational load of the proposed SLMKBALE algorithm is much lower than that of the LMKBALE (least mean kurtosis based adaptive line enhancer) and as many as that of LMSBALE (least mean square based adaptive line enhancer), and the SLMKBALE algorithm has better ability to hand non-Gaussian and enhancing signal spectrum in comparison with the LMSBALE, SLMSBALE (signed LMSBALE), LMFBALE (least mean fourth based adaptive line enhancer) and LMKBALE algorithm and that the mean square error (MSE) of the proposed algorithm is the lowest in all algorithms when the MSE converges. Therefore, the SLMKBALE algorithm is useful and reliable