On the periodically time-varying bias in adaptive feedback cancellation systems with frequency shifting

Guo, Meng; Kuenzle, Bernhard

doi:10.1109/icassp.2016.7471733

Cited by 9 publications

(10 citation statements)

References 14 publications

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“…In a recent study [14], it was shown that even if the frequency shifting is effective in decorrelating the signals x(n) and u(n) and hence it contributes to an unbiased estimation ofĥ(n), the combination of adaptive filter and frequency shifting introduces another and signal dependent periodically time-varying residual bias; although much smaller compared to the original bias in the adaptive filter estimation without The residual bias has also a frequency of 10 Hz and it can be significantly reduced when using a gradient correction (dashdotted line) [14], which is though not considered in this work.…”

Section: Introductionmentioning

confidence: 93%

“…In this section, we review the residual bias problem, originally described in [14], which is the consequence of using adaptive filter and the frequency shifting together.…”

Section: Review Of Residual Biasmentioning

confidence: 99%

“…To reduce the negative effect of the acoustic feedback problem, a modern approach is to use adaptive filters in a system identification setup. Some examples of using the adaptive filters can be found in [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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A Method for Determining Periodically Time-Varying Bias and Its Applications in Acoustic Feedback Cancellation

Guo

2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Adaptive filters have been widely used for feedback cancellation in audio systems including hearing aids. In addition to adaptive filters, the frequency shifting has often been used to obtain an unbiased estimation of the adaptive filters, by decorrelating the incoming and outgoing signals of the audio system. However, it has been shown in a recent study, that although the frequency shifting technique is effective in decorrelating the signals, its use in addition to the adaptive filter would introduce an additional and signal dependent periodically time-varying bias also referred to as the residual bias, especially for tonal signals such as music. In this work, we make use of that knowledge and propose a method to detect different acoustic situations, based on the level of residual bias. We further discuss on some control actions to be taken in acoustic feedback cancellation systems upon these detections. Finally, we demonstrate the behavior of the residual bias and the detection of different acoustic feedback situations in an example computer simulation.

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Section: Introductionmentioning

confidence: 93%

“…In this section, we review the residual bias problem, originally described in [14], which is the consequence of using adaptive filter and the frequency shifting together.…”

Section: Review Of Residual Biasmentioning

confidence: 99%

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A Method for Determining Periodically Time-Varying Bias and Its Applications in Acoustic Feedback Cancellation

Guo

2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…This equation (1)(2)(3)(4)(5)(6)(7)(8)(9) leads to the motivation for defining the PSD in (1-8). The PSD can also be defined as:…”

Section: Power Spectral Densitymentioning

confidence: 99%

“…Guo et al [7] investigated the outcome of frequency shifting in an acoustic feedback control system. This work recommends a solution to achieve an unbiased approximation by eliminating the slowly time variable part in adaptive filter estimation.…”

Section: Existing Surveymentioning

confidence: 99%

Integrated Framework to Study Efficient Spectral Estimation Techniques for Assessing Spectral Efficiency Analysis

Prasad¹,

Suresh²

2017

ijacsa

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Abstract-The advanced network applications enable software driven spectral analysis of non-stationary signal or processes which precisely involves domain analysis with the purpose of decomposing a complex signal coefficients into simpler forms. However, the proper estimation of power coefficients over frequency components of a random signal leads to provide very useful information required in various fields of study. The complex design constraints associated with conventional parametric models such as Dynamic Average Model, Autoregressive MA, etc. for multidimensional spectral estimation using adaptive filters leads to a situation where higher computational complexities generate significant overhead on the systems. Therefore, the proposed study aims to formulate an efficient framework intended to derive a fast algorithm for processing Adaptive Capon and Phase Estimator (APES). The proposed method is applied to a non-stationary signal which is random. Further, the adaptive estimation of power spectra along with more accurate spectral efficiency has been identified in case of APES. An extensive performance evaluation followed by a comparative analysis has been performed by obtaining the values from different spectral estimation techniques, such as APES, PSC, ASC, and CAPON. Moreover, the framework ensures that unlike others, APES is subjected to attain superior signal quality regarding Power Spectral Density (PSD) and Signal to Noise Ratio (SNR) while achieving very less amount of Mean Square Error (MSE). It also exhibits comparatively low convergence speed and computational complexity as compared to its legacy versions.

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Adaptive feedback control using improved variable step-size affine projection algorithm for hearing aids

Tran

Schepker

Doclo

et al. 2017

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

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On the periodically time-varying bias in adaptive feedback cancellation systems with frequency shifting

Cited by 9 publications

References 14 publications

A Method for Determining Periodically Time-Varying Bias and Its Applications in Acoustic Feedback Cancellation

A Method for Determining Periodically Time-Varying Bias and Its Applications in Acoustic Feedback Cancellation

Integrated Framework to Study Efficient Spectral Estimation Techniques for Assessing Spectral Efficiency Analysis

Adaptive feedback control using improved variable step-size affine projection algorithm for hearing aids

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