Mean-square performance of the hyperslab-based adaptive projected subgradient method

This paper is concerned with the mean-square performance of the hyperslab-based adaptive projected subgradient method, a set theoretic estimation tool that has been successfully applied in a wide variety of signal processing tasks. Using energy-conservation arguments, general performance results are derived without restricting the regression data to being Gaussian or white. Numerical simulations are provided to illustrate the theoretical developments.