An alternative formulation for low rank transform domain adaptive filtering

Linebarger et al. (see Proceedings of Thirty-First Asilomar Conference on Signals, Systems & Computers, Pacific Grove, California, USA, vol.1, p.123-27, 1997) introduced a new, optimal approach to low rank transform domain adaptive filtering is , using a least squares, matrix based framework. Further, Raghothaman (see Proceedings of 8th IEEE DSP Workshop, Utah, USA, 1998) provides a computationally efficient algorithm to solve the formulation of the problem proposed by Linebarger. In this paper, we examine an alternative method for applying an optimal low rank transform, within the framework derived by Linebarger, to convert an overdetermined, full rank system into a low rank system. In addition, we propose a computationally efficient algorithm for the implementation of our method, using the DCT as the unitary transformation. Finally, we evaluate the performance of our algorithm via simulation in an acoustic echo canceller application, and show that the performance of our method is superior to existing low rank methods, NLMS and affine projection.