Efficient Recursive Total Least Mean Fourth Algorithm

In this work, an iterative total least mean fourth (TLMF) algorithm is devised to solve adaptive filtering problems when both the input and output signals are corrupted with noise. The proposed algorithm is based on a stochastic approach related to the existing total least mean square (TLMS) algorithm. The cost function of the TLMF is defined in terms of the fourth power of the error and minimized iteratively to reach the optimal weight solution. The unknown system is evaluated at various levels of signal-to-noise ratio (SNR). The simulation results showed that the proposed algorithm produced interesting results when both the noise is white or coloured.