  In many application of noise cancellation, the changes in signal
characteristics could be quite fast. This requires the utilization of adaptive
algorithms, which converge rapidly. Least Mean Squares (LMS) adaptive filters
have been used in a wide range of signal processing application. The Recursive
Least Squares (RLS) algorithm has established itself as the "ultimate" adaptive
filtering algorithm in the sense that it is the adaptive filter exhibiting the
best convergence behavior. Unfortunately, practical implementations of the
algorithm are often associated with high computational complexity and/or poor
numerical properties. Recently adaptive filtering was presented that was based
on Matching Pursuits, have a nice tradeoff between complexity and the
convergence speed. This paper describes a new approach for noise cancellation
in speech enhancement using the new adaptive filtering algorithm named fast
affine projection algorithm (FAPA). The simulation results demonstrate the good
performance of the FAPA in attenuating the noise.
