Efficiency of Oversampled Discrete Fourier Transform Filter Blocks to Cancel Background Noise

Abstract

Slow focus ability and complex computations are the main barrages facing the usage of adaptive noise filtering for cancellation of
the background noise. Here we have developed noise canceller by using two fold over sampled filter banks. We had formulated
the system by few realistic assumptions to analyses the filter. System offers a structure without cross-filters or gap filter banks
and hence decreases the residual noise at the output. Increasing initial convergence rate is addressed and computational complexity
is analyzed .The performance under white and colored environments, is evaluated in terms of mean square error performance. As
a result fast initial convergence was resulted. An increase in the amount of noise reduction by approximately 5dB compared to
full-band model reached under actual speech and background noise. In spite of the insertion of analysis/synthesis filter banks, the
proposed noise canceller is still computationally efficient.