Abstract
To achieve good estimation in the impulsive noise environment, some hyperbolic functions have been introduced as cost functions to develop robust adaptive filtering algorithms in recent years. However, the hyperbolic functions have rarely been studied for complex-valued signals. In this paper, a robust adaptive algorithm is introduced for processing both circular and non-circular complex-valued signals by utilizing the complex hyperbolic secant cost functions. Moreover, its performance is thoroughly analyzed, including mean convergence, mean-square transient behavior, and mean-square steady-state behavior. Finally, the simulation results show the advantages of the proposed algorithm for complex-valued signal processing in non-Gaussian environments and verify the accuracy of the theoretical performance analysis.
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