On Active Noise Control Systems With Online Acoustic Feedback Path Modeling

Akhtar, Muhammad Tahir; Abe, Masahide; Kawamata, Masayuki

doi:10.1109/tasl.2006.876749

Cited by 54 publications

(46 citation statements)

References 18 publications

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“…2 (b). As in previous methods [5,6,7], a random noise signal v(n), uncorrelated with the reference signal x(n) is added with the output y(n) of W (z). The sum [y(n) + v(n)] is propagated by the canceling loudspeaker.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…This method achieves improved online FBPM, however, there are a few problems: 1) the performance depends on the proper choice of the decorrelation delay, and 2) it works only for predictable noise sources. To overcome these problems, in [7] authors have proposed a method using adaptive noise cancelation (ADNC) filter in place of the discrimination filter in [6]. The main advantage of this method is that it can work for both predictable and un-predictable noise sources.…”

Section: Anc Systems With Online Feedback Path Modelingmentioning

confidence: 99%

“…Here we compare the performance of the proposed method with the Kuo's method [6], and authors' previous work [7]. For acoustic paths the experimental data provided by [1] is used.…”

Section: Computer Simulations and Concluding Remarksmentioning

confidence: 99%

“…A detailed review of existing FIR-filter-based methods [4,5,6] for online FBPM can be found in [7]. In this paper, we describe only the best existing method proposed by Kuo in [6], identify its problems, and then describe the proposed method in comparison with the authors' previous work of [7]. The main objective is to achieve improved performance at reduced computational complexity.…”

Section: Introductionmentioning

confidence: 99%

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Acoustic feedback neutralization in active noise control systems

Akhtar

Tufail

Abe

et al. 2007

IEICE Electron. Express

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This letter proposes a method for active noise control (ANC) systems with online acoustic feedback neutralization. The proposed method is a modified version of authors' previous work, and the objective here is to reduce the computational complexity. This is achieved by combining the role of feedback path modeling and neutralization filters. The computer simulations are carried out which demonstrate that the proposed method achieves better performance than the existing methods and at somewhat reduced computational cost.

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Section: Proposed Methodsmentioning

confidence: 99%

Section: Anc Systems With Online Feedback Path Modelingmentioning

confidence: 99%

“…Here we compare the performance of the proposed method with the Kuo's method [6], and authors' previous work [7]. For acoustic paths the experimental data provided by [1] is used.…”

Section: Computer Simulations and Concluding Remarksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Acoustic feedback neutralization in active noise control systems

Akhtar

Tufail

Abe

et al. 2007

IEICE Electron. Express

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show abstract

“…One of the study [28] based on FXLMS analysed the algorithm and extended the new algorithm to reduce the multi-tonal noise. Similar work was developed in [29] and evaluated with narrowband and broadband noise against the instability in convergence of adaptation algorithm. The modified FXLMS algorithm based on efficient affine projection technique is compared with conventional FXLMS algorithm in [30].…”

Section: Active Noise Cancellationmentioning

confidence: 99%

Speech Enhancement Techniques: Quality vs. Intelligibility

Nemade¹,

Shah²

2014

IJFCC

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Abstract-With the rapid advancements in industrial and technology applications, the demand from consumer for transmission and manipulation of data, primarily -speech, audio and images, are at its peak. The speech, being a fundamental way of communication for the humans, has been embedded in various essential applications like speech recognition, voice-distance-talk and other forms of personal communications. There are so many applications of speech still to be far from reality just because of lack of efficient and reliable noise removal mechanism and preserving or improving the intelligibility for the speech signals. The broad categories of speech enhancement techniques can be listed as speech filtering techniques, beam forming techniques and active noise cancellation methods. In this paper, an attempt has been stepped towards surveying the methodologies for speech improvement. It is also interesting to investigate, how these techniques affect the performance of various application systems like speech recognition and speech communication. Essentially, we also discuss about the types and sources of noise that can be considered in speech enhancements. Index Terms-Enhancement, beamforming and active noise cancellation, single channel enhancement I. INTRODUCTIONSpeech is the fundamental and common medium, hence important for us, to communicate and most effective and reliable means for expressing oneself for personal communication. With advancement in hardware technologies, there are so many electronic and mobile personal communication based devices available, today in market and that too in cheaper cost and with easy availability. The applications like speech recognition, mobile and personal communication, public address system are few of the applications from long list of speech based systems. However, undesired noises in environment like sound from heavy machines, vehicles are also present in one or other form everywhere. These noises cause undesired effects in speech transmission and acquiring systems. Recently, restricted or usable vicinity of applications is moving from one place and close room to more open and multiple locations, leading to several of types undesired signals of mixing with desired speech signal making speech more corrupt with noise. Not only human communications but intelligent machines which Manuscript received September 14, 2013; revised November 12, 2013 trying to automate the things and sometimes also takes decision based on what it receives as a speech, also suffers from the degraded performance.Since last five decades, various approaches for noise reduction and speech enhancements have been investigated and developed. Among, very early and fundamental approach of noise reduction was introduced to use the theory of the optimum Wiener filter. Given a desired signal and an input signal, the Wiener filter produces an estimate of the desired signal that is optimal, i.e. the squared mean error or difference between the signals is minimized. The Wiener filter can also be adaptively estimated us...

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Frequency domain analysis of the mirror‐modified filtered‐x least mean squares algorithm with low ambient noise

Lopes

Gerald

2021

Adaptive Control & Signal

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Summary The mirror‐modified filtered‐x least mean squares (MMFxLMS ) algorithm is a variation of the FxLMS algorithm with online secondary path modeling that cannot diverge due to secondary path modeling errors. However, problems may occur when the ambient noise is not limited due to insufficient modeling power. This work shows that under a frequency domain analysis without ambient noise, the MMFxLMS algorithm is always stable, and expressions for the maximum residual noise level at any given time are obtained. It is also shown that, under the same context, convergence to the minimum residual noise is guaranteed. Still, convergence can be much slower for high secondary path modeling errors than that of the LMS or MFxLMS algorithms. Simulations confirm these results.

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On Active Noise Control Systems With Online Acoustic Feedback Path Modeling

Cited by 54 publications

References 18 publications

Acoustic feedback neutralization in active noise control systems

Acoustic feedback neutralization in active noise control systems

Speech Enhancement Techniques: Quality vs. Intelligibility

Frequency domain analysis of the mirror‐modified filtered‐x least mean squares algorithm with low ambient noise

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