A class of memoryless robust detectors in dependent noise

A new general approach to the formulation of a detector in non-Gaussian noise satisfying the strong mixing condition is introduced. The only statistical knowledge required for the optimal design is a set of parameters which can be estimated from data and recursively updated. This eliminates the requirement that exact distributions be known and leads naturally to efficient adaptive detectors.<
>