A Newton-like algorithm for complex variables with applications in blind equalization

Although Newton algorithm has been extended to the complex domain in different forms, none of them seems to be directly applicable to blind equalization. Therefore, the objective of this correspondence is to develop an algorithm for blind equalization in the complex domain. We propose a Newton-like algorithm based on a complex Taylor series. Stochastic Newton-like algorithms (SNLA) for two blind equalization cost functions are developed. Simulations show that the new algorithms perform slightly better than the self-orthogonalizing algorithm.