On the Convergence Behavior of Affine Projection Algorithm with Direction Error

Abstract

An affine projection algorithm with direction error (AP-DE) is presented to solve the nonconformity between the iterated direction of the adaptive filter and the direction caused by the iteration error. A statistical analysis model is shown to analyze the AP-DE algorithm for autoregressive input signals. Deterministic recursive equations for the mean weight error and for the mean-square error in the iterated direction are derived. We also analyze the steady-state mean-square error in the iterated direction for the AP-DE algorithm. Simulation results are provided to corroborate the analytical results.

Statistical Tracking Behavior Analysis for the Affine Projection Algorithm Based on Direction Error

“…The statistical analysis of convergence model for the AP algorithm has been shown by using the (AR) input model [16][17][18]. Under the assumption given by [12,13], the convergence model was shown for the kind of AP-DE algorithm in [19]. When the step size was equal to one, the statistical tracking behavior was given for the AP-DE algorithm [20], in which the MWE and MSE behaviors are analyzed.…”

A Fault Detection Filtering for Networked Control Systems Based on Balanced Reduced-Order

“…This property motivates us to seek a high performance realization in the fault detection for the NCS. Some results show that the characteristics of the parameterization play an important role in minimizing the output error [8,9]. Since the balanced realization, introduced by [10], has a good noise rejection characteristic, this property should lead the fault detection systems exhibiting well robust to the data packet dropout for the NCS.…”