A new subband weight transform for delayless subband adaptive filtering structures

In applications like echo cancellation and speech enhancement, where there is need to track changes continuously, adaptive filtering is usually used. Long adaptive filters gives problems like slow convergence and high complexity. Subband adaptive filtering has been introduced to overcome these problems. The filter banks used in subband adaptive filtering introduce large delays. In order to compensate for the delays, delayless subband adaptive filtering is introduced. Delayless subband adaptive filtering is used in both open loop and closed loop configuration, where the subband filters are transformed to a fullband filter using a weight transform. This paper proposes a new subband weight transform based on the filter banks that are used. We investigate the performance of the weight transform using Monte Carlo simulations of a system identification situation. Different adaptive algorithms are used to compare the weight transform to previously proposed weight transforms.