A generalization of the sparse iterative covariance-based estimator
In this work, we extend the popular sparse iterative covariance-based estimator (SPICE) by generalizing the formulation to allow for different norm constraint on the signal and noise parameters in the covariance model. For any choice of norms, the resulting generalized SPICE method enjoys the same benefits as the regular SPICE method, including being hyperparameter free, although the choice of nor
