Performance Analysis of an Adaptive SubspaceFilter for Signal
نویسنده
چکیده
| In this paper, we investigate the noise suppression performance of a novel adaptive lter based on sub-space methods. In contrast to conventional subspace lters, this approach requires no eigenvalue or singular value decomposition. Therefore, our adaptive subspace lter can be implemented for real-time operation using general purpose digital signal processors. In addition, only the noisy signal, and no reference signal is needed. We compare the adaptive subspace lter (ASF) with the adaptive line enhancer (ALE) which also requires no reference signal. For stationary signals the noise suppression performance is similar to that of the ALE. However, in a non-stationary environment the ASF exhibits far better tracking behavior, and faster convergence rate.
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