A new variable tap-length LMS algorithm to model an exponential decay impulse response

This letter proposes a new variable tap-length least-mean-square (LMS) algorithm for applications in which the unknown filter impulse response sequence has an exponential decay envelope. The algorithm is designed to minimize the mean-square deviation (MSD) between the optimal and adaptive filter weight vectors at each iteration. Simulation results show the proposed algorithm has a faster convergence rate as compared with the fixed tap-length LMS algorithm and is robust to the initial tap-length choice

Handling noise signal features extracted from an additional five devices.

<p>All signal features were averaged over all handling noises generated for each device. 95% confidence limits are also presented.</p

Handling noise signal features extracted from the three devices used in the psychoacoustic tests.

<p>All signal features were averaged over all handling noises generated for each device. 95% confidence intervals are also presented.</p

Mean opinion score on the degradation scale vs signal to noise ratio.

<p>Dots: average for each sample. Red line: estimation using ordinal regression model. Black line: polynomial fit to the ordinal regression model.</p

Example spectrograms of rubbing type microphone handling noises.

<p>Recorded on the a) SM58, the b) iPhone and the c) AT803b.</p

Example spectrograms of tapping type microphone handling noises.

<p>Recorded on the a) SM58, the b) iPhone and the c) AT803b.</p

Examples waveforms of microphone handling noises recorded on an iPhone 4.

<p>a) Tapping and b) rubbing type handling noises.</p