An adaptive recursive algorithm based on non-quadratic function of the error

In adaptive filtering, several algorithms were developed to get faster convergence and lower misadjustment, but rely on second order statistics which are optimum only for Gaussian signals. In this work we propose a recursive filter by modifying the performance surface to a non-quadratic function applied upon the error. As a result, the equations are simple, elegant, and yielded faster convergence and lower misadjustment when compared to the RLS, keeping equivalent computational cost.