Minimax and L_{1} curve fitting in non-Gaussian MAP estimation
Paul J. Scott · IEEE Transactions on Automatic Control · 1975
A class of non-Gaussian estimation problems is equivalent to minimax and L1curve fitting. The curve fit is shown to be algebraically dual to optimization of a positive semidefinite quadratic form with linear inequalities, which is solved by a fast quadratic program based on Graves' simplex algorithm. An example compares the performance of this estimator with the (suboptimal) minimum mean-squared error (MMSE) estimations generated by quadratic curve fitting.