Adaptive FIR filtering based on bounded error constraints

The performance of adaptive FIR algorithms in the presence of bounded disturbances, in particular, algorithms based on gradient mean squared error (MSE) estimators, gradient estimators with dead-zone thresholds, and set membership estimators, is examined. A simple example of the bursting phenomenon is given, and the algorithms and their properties are described. Analytical results on the performance of these estimators are also given. An algorithm that provides both MSE and instantaneous maximum amplitude error (in the limsup sense) performance guarantees is proposed