A transform domain second-order recursive inverse adaptive algorithm
Mohammad Shukri Salman, Alaa Eleyan, Bahaa Al-Sheikh
The second-order recursive inverse (RI) adaptive algorithm has been showing a better performance than that of the well-known recursive-least-squares (RLS) algorithm with reduced comparable computational complexity. Although the second-order RI algorithm provides significant performance, it suffers from low convergence rate in some situations where a relatively low initial step-size is required. In this paper, we propose a new second-order RI algorithm that applies a discrete wavelet transform (DWT) to the input signal. This transformation reduces the self-correlation of the input signal which, in turn, overcomes the low convergence rate of the second-order RI algorithm when a relatively small initial step-size is used. The performance of the proposed algorithm is compared to those of the RI, second-order RI and RLS algorithms in different Gaussian and impulsive noise environments in a noise cancellation setting. The simulations show that the proposed algorithm has superior convergence rate compared to those algorithms.
impulsive noise; noise cancellation; RI algorithm; RLS algorithm; wavelet transform;