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12.03 Signal Processing for Active Control

A conjugate gradient least square based method for sound field control
Time: 7:20 pm

Author: Pierangelo Libianchi

Abstract ID: 1736

In sound field control, a set of control sources is used to match the pressure field generated by noise sources but with opposite phase to reduce the total sound pressure level in a defined area commonly referred to as dark zone. This is usually an ill-posed problem. The approach presented here employs a subspace iterative method where the number of iterations acts as the regularization parameter and controls unwanted side radiation, i.e. side lobes. More iterations lead to less regularization and more side lobes. The number of iterations is controlled by problem-specific stopping criteria. Simulations show the increase of lobing with increased number of iterations. The solutions are analysed through projections on the basis provided by the source strength modes corresponding to the right singular vector of the transfer function matrix. These projections show how higher order pressure modes (left singular vectors) become dominant with larger number of iterations. Furthermore, an active-set type method provides the constraints on the amplitude of the solution which is not possible with the conjugate gradient least square algorithm alone.

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Multi-channel feedforward active noise control system for reducing snore noise with snore noise-term detection
Time: 6:40 am

Author: Koki Nakamura

Abstract ID: 1755

In this paper, a multi-channel feedforward active noise control system for reducing snore noise with noise-term detection is proposed.  The snore noise consists of a noise-term and a silent-term, and it is difficult to reduce the snore noise by the active noise control system. Since the conventional multi-channel feedforward active noise control system updates the noise control filters even in the silent-term, the conventional active noise control system updates the noise control filters unnecessarily. Therefore, the proposed multi-channel feedforward active noise control system introduces threshold processing to update the noise control filters only in the noise-term. Owing to this process, it is possible to reduce the update count of the noise control filters. Simulation results show that the proposed active noise control system can reduce the snore noise as same as the conventional active noise control system and can reduce the update count of the noise control filters compared to the conventional active noise control system.

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A constrained optimal hear-through filter design approach for earphones
Time: 2:40 pm

Author: Yongjie Zhuang

Abstract ID: 1816

The sound from environment will be altered after it transmits through headphones to the ear canal. A hear-though filter can be designed and implemented in the headphones to create a more natural hearing experience, i.e., offer a transparent mode for headphones. The design of hear-through filter is also required in some other applications, e.g., augmented reality audio. In this paper, a constrained hear-through filter design approach is proposed. It is firstly shown that the hear-through filter design problem can be formulated in a similar form to active noise control filter design in the frequency domain. One advantage of this design approach is that multiple practical constraints can be applied conveniently by formulating a constrained optimization problem. Then the constrained optimization problem for hear-through filter design is reformulated as cone programming problem which can be solved efficiently. The proposed design approach can also specify the desired delay of reproduced sound. The designed filter can be directly implemented in an active noise control system in the headphone such that the requirement for extra electronic components can be minimal.

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Acoustic analysis of snoring sound from different microphones
Time: 6:20 am

Author: li ding

Abstract ID: 1962

Snoring is a common symptom of obstructive sleep apnea-hypopnea syndrome. The results show that there are obvious differences for most microphones in terms of the data distribution of features in the time and frequency domain. The results of snoring analysis from different recordings devices would be totally divergent. In view of this, when developing snoring analysis devices based user selected microphones (i.e. smartphone) recorded, we should take into account the discrepancy between different microphones.

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Simulation of LMS based adaptive noise cancellation using Labview
Time: 2:20 pm

Author: Maja Anachkova

Abstract ID: 2128

The audio signals processed in the signal measurement systems are inevitably susceptible to unwanted noise which significantly affects the quality of the signal and the overall performance of the signal communication systems. Due to its’ random and unpredictable nature, the amount of noise in signals has proven to be a significant issue in designing these systems and recently has been a trending research topic. In this regard, the active noise cancellation method has proven to be an effective technique for eliminating the noise effects on signal processing. The concept of active noise cancellation is based on the application of adaptive filters and algorithms proposed to reduce the signal corruption and distortion caused by the noise due to the principle of destructive interference. In this paper a simulation model of active noise reduction technique using the LMS (Least Mean Square) algorithm in Labview is presented. The purpose of the work is to investigate the noise cancellation effect on a recorded audio file in terms of analyzing the audio file before and after filtering out the noise by using the LMS algorithm and discuss the results thereof.

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Semi-adaptive active noise cancellation headphones
Time: 2:00 pm

Author: Song Li

Abstract ID: 2808

Active noise cancellation (ANC) headphones are becoming increasingly important as they can effectively attenuate perceived ambient noise. Fixed filters are commonly applied in commercially available ANC headphones due to their robustness. However, they are not capable of adapting to changes that occur in dynamic environments, resulting in degraded ANC performance. In contrast, adaptive filters are able to update the ANC filters to compensate for noise in dynamic environments, but large estimation errors can occur due to a sudden change in direction/type of noise or secondary path. Some studies have suggested an ANC system by combining fixed and adaptive filters. Based on this mechanism, we propose a semi-adaptive ANC system in which the fixed and adaptive filters are weighted in real-time. Initially, the weighting for the fixed filter dominates the whole system to ensure the robustness of the ANC system. Then, the residual error provided by the adaptive filter is simulated and compared to the real measured one to determine the relative weighting between the fixed and adaptive filters. In this study, this approach is applied to a feedback ANC system. Simulation results show that our proposed approach achieves high noise attenuation performance while maintaining robustness with time-varying secondary paths.

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