Search

Convex combination of two adaptive filters is an efficient method to improve adaptive filter performances. In this paper, a subband convex combination method of two adaptive filters for fast convergence rate in the transient state and low steady state error is presented. The cost function of mixing parameter for a subband convex combination is defined, and from this, the coefficient update equation is derived. Steady state analysis is used to prove the stability of the subband convex combination. Some simulation examples in system identification scenario show the validity of the subband convex combination schemes.

It is well known, combination scheme is suitable for improving the performance of adaptive algorithms. In this paper, we propose a subband combination scheme for sparse impulse response systems. The combination is carried out in subband domain. In this convex combination, SIPNLMS and SNLMS are derived for fast convergence and small steady state error respectively. And mixing parameters are described by minimum mean square error and stochastic gradient algorithm. In adaptive system identification scenario, the advantages of this proposed method are illustrated.

It is very important to detect power quality disturbances effectively in power quality monitoring. In industrial and commercial power systems, voltage sags, voltage swells, transients, and interruptions are main disturbances which affect sensitive equipments. This paper presents a signal processing technique which combines filter bank system and adaptive filter for power quality disturbances detection and localization. In this method, the filter bank system which has binary tree structure is designed for decomposing input power signal to subband signal components. In each subband, adaptive filters are operated as predictor, and the residual values of each adaptive predictor are used to detect power quality disturbances. The usefulness of the proposed method is demonstrated by synthesized signals harmonically.