On the optimality of subband adaptive filters

In this paper, we derive a polyphase analysis to determine the optimum filters in a subband adaptive filter (SAF) system. The structure of this optimum solution deviates from the standard SAF approach and presents its best possible solution only as an approximation. Besides this new insight into SAF error sources, the discussed analysis allows to calculate the optimum subband responses and the standard SAF approximation. Examples demonstrating the validity of our analysis and its use for determining SAF errors are presented

Performance limitations of subband adaptive filters

In this paper, we evaluate the performance limitations of subband adaptive filters in terms of achievable final error terms. The limiting factors are the aliasing level in the subbands, which poses a distortion and thus presents a lower bound for the minimum mean squared error in each subband, and the distortion function of the overall filter bank, which in a system identification setup restricts the accuracy of the equivalent fullband model. Using a generalized DFT modulated filter bank for the subband decomposition, both errors can be stated in terms of the underlying prototype filter. If a source model for coloured input signals is available, it is also possible to calculate the power spectral densities in both subbands and reconstructed fullband. The predicted limits of error quantities compare favourably with simulations presented

Subband adaptive filtering for acoustic echo control using allpass polyphase IIR filterbanks

Published versio

Efficient time delay estimation and compensation applied to the cancellation of acoustic echo

The system identification problem is notably dealt with using adaptive filtering approaches. In many applications the unknown system response consists of an initial sequence of zero-valued coefficients that precedes the active part of the response. The presence of these coefficients introduces a flat delay in the incoming signals which can take significantly large values. When most adaptive approaches attempt to model such a system, the presence of flat delay impairs their operation and performance. The approach introduced in this thesis aims to model the flat delay and active part of the unknown system separately. An efficient system for time delay estimation (TDE) is introduced to estimate the flat delay of an unknown system. The estimated delay is then compensated within the adaptive system thus allowing the latter to cover the active part ofthe unknown system. The proposed system is applied to the Acoustic Echo Cancellation (ABC) problem

Doctor of Philosophy

dissertationHearing aids suffer from the problem of acoustic feedback that limits the gain provided by hearing aids. Moreover, the output sound quality of hearing aids may be compromised in the presence of background acoustic noise. Digital hearing aids use advanced signal processing to reduce acoustic feedback and background noise to improve the output sound quality. However, it is known that the output sound quality of digital hearing aids deteriorates as the hearing aid gain is increased. Furthermore, popular subband or transform domain digital signal processing in modern hearing aids introduces analysis-synthesis delays in the forward path. Long forward-path delays are not desirable because the processed sound combines with the unprocessed sound that arrives at the cochlea through the vent and changes the sound quality. In this dissertation, we employ a variable, frequency-dependent gain function that is lower at frequencies of the incoming signal where the information is perceptually insignificant. In addition, the method of this dissertation automatically identifies and suppresses residual acoustical feedback components at frequencies that have the potential to drive the system to instability. The suppressed frequency components are monitored and the suppression is removed when such frequencies no longer pose a threat to drive the hearing aid system into instability. Together, the method of this dissertation provides more stable gain over traditional methods by reducing acoustical coupling between the microphone and the loudspeaker of a hearing aid. In addition, the method of this dissertation performs necessary hearing aid signal processing with low-delay characteristics. The central idea for the low-delay hearing aid signal processing is a spectral gain shaping method (SGSM) that employs parallel parametric equalization (EQ) filters. Parameters of the parametric EQ filters and associated gain values are selected using a least-squares approach to obtain the desired spectral response. Finally, the method of this dissertation switches to a least-squares adaptation scheme with linear complexity at the onset of howling. The method adapts to the altered feedback path quickly and allows the patient to not lose perceivable information. The complexity of the least-squares estimate is reduced by reformulating the least-squares estimate into a Toeplitz system and solving it with a direct Toeplitz solver. The increase in stable gain over traditional methods and the output sound quality were evaluated with psychoacoustic experiments on normal-hearing listeners with speech and music signals. The results indicate that the method of this dissertation provides 8 to 12 dB more hearing aid gain than feedback cancelers with traditional fixed gain functions. Furthermore, experimental results obtained with real world hearing aid gain profiles indicate that the method of this dissertation provides less distortion in the output sound quality than classical feedback cancelers, enabling the use of more comfortable style hearing aids for patients with moderate to profound hearing loss. Extensive MATLAB simulations and subjective evaluations of the results indicate that the method of this dissertation exhibits much smaller forward-path delays with superior howling suppression capability