Sequential M-estimation

We propose a sequential M-estimation algorithm as an alternative to sequential least squares. Being an approximation of the exact M-estimator, the proposed technique is robust to nonGaussian processes and outperforms sequential least squares. Simulation results demonstrate the power of the proposed sequential M-estimator.

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