Integrated active noise control for open-fit hearing aids with customized filter
TL;DR: A customized filter based on the hearing threshold of hearing-impaired patient is designed to generate the anti-noise only in audible frequency range to increase efficiency and save power consumption of hearing aids.
Abstract: The open-fit hearing aids that allow air and sound into the ear canal have become popular in recent years. Unfortunately, they result in the noise leakage problem that bypasses the hearing aids toward the eardrum and will degrade the quality of desired signal. This paper proposes a modified audio-integrated adaptive feedback active noise control (ANC) system for open-fit hearing aids. Traditionally, the ANC system attenuates the total power of the unwanted noise over the entire spectrum. To increase efficiency and save power consumption of hearing aids, we design a customized filter based on the hearing threshold of hearing-impaired patient to generate the anti-noise only in audible frequency range. The performance of the proposed method is verified by both computer simulations and real-time experiments.
Citations
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TL;DR: In this paper, the strength of recently introduced nature inspired heuristic computing technique named fireworks algorithms (FWA) and its variants are exploited in the field of system identification based on active noise control (ANC) systems.
Abstract: In this paper, strength of recently introduced nature inspired heuristic computing technique named fireworks algorithms (FWA) and its variants are exploited in the field of system identification based on active noise control (ANC) systems. Residual error based fitness function is constructed for ANC system and optimization of parameter is carried out with the help of fireworks, enhance fireworks and adaptive fireworks algorithms. The design scheme is applied to number of scenarios of ANC system for different primary and secondary paths. The designed methodology is evaluated for three different noise interferences based on sinusoidal and random signals. The scheme validated by means of accuracy and convergence operators through the results of statistics based on ample number of independent trails. The comparative study of results is also made for three variants of FWA to establish their worth in terms of precision, stability and complexity measures.
15 citations
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TL;DR: A selective fixed-filter active noise control algorithm, which selects a pretrained control filter to attenuate the detected primary noise rapidly and is shown to exhibit a satisfactory response time and steady-state noise reduction performance, even for time-varying noise and real non-stationary disturbance.
Abstract: Conventional real-time active noise control (ANC) usually employs the adaptive filtered-x least mean square (FxLMS) algorithm to approach optimum coefficients for the control filter. However, lengthy training is usually required, and the perceived noise reduction is not immediately realized. Motivated by the practical implementation, we propose a selective fixed-filter active noise control (SFANC) algorithm, which selects a pretrained control filter to attenuate the detected primary noise rapidly. On top of improved robustness, the complexity analysis reveals that SFANC appears to be more efficient. The SFANC algorithm chooses the most suitable control filter based on the frequency-band-match approach implemented in a partitioned frequency-domain filter. Through simulations, SFANC is shown to exhibit a satisfactory response time and steady-state noise reduction performance, even for time-varying noise and real non-stationary disturbance.
12 citations
Cites background from "Integrated active noise control for..."
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TL;DR: A novel recurrent interval type-2 fuzzy brain emotional learning filter (RT2BELF) is proposed for achieving favourable filtering performance and the superiority of the proposed method is confirmed by the results comparison with some noise cancellation methods.
Abstract: This article aims to develop a more efficient adaptive filter for the active noise cancellation (ANC). A novel recurrent interval type-2 fuzzy brain emotional learning filter (RT2BELF) is proposed for achieving favourable filtering performance. The ANC is a method to eliminate noise by creating an anti-noise signal which has the same magnitude but opposite phase with the unwanted noise. In order to adapt to the change of the noise, the parameters for the RIT2BELF are online updated based on the adaptive laws, which are derived by the steepest descent gradient approach. The performance of the proposed ANC design method is successfully demonstrated based on numerical simulation results in the real signals. Finally, the superiority of the proposed method is confirmed by the results comparison with some noise cancellation methods.
8 citations
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TL;DR: The block coordinate descent McFxLMS (BCD McFXLMS) algorithm proposed in this paper substantially reduces the computation cost of an MCANC system, while maintaining the same noise reduction performance as the conventional McFxlMS algorithm.
Abstract: Multichannel active noise control (MCANC) is widely regarded as an effective solution to achieve a significantly large noise-cancellation area in a complicated acoustic field. However, the computational complexity of MCANC algorithms, such as the multichannel filter-x least mean square (McFxLMS) algorithm, grows exponentially with an increased channel count. Many modified algorithms have been proposed to alleviate the complexity but at the expense of noise reduction performance. Till now, the trade-off between computational complexity and noise reduction performance has limited the practical implementation of MCANC. The block coordinate descent McFxLMS (BCD McFxLMS) algorithm proposed in this paper substantially reduces the computation cost of an MCANC system, while maintaining the same noise reduction performance as the conventional McFxLMS algorithm. Furthermore, a momentum mechanism is integrated into the BCD McFxLMS in practice to improve the convergence speed. The simulation and experimental results validate the effectiveness of proposed algorithms when dealing with noise in a realistic environment.
6 citations
References
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TL;DR: A beamforming structure is presented which can be used to implement a wide variety of linearly constrained adaptive array processors and is shown to incorporate algorithms which have been suggested previously for use in adaptive beamforming as well as to include new approaches.
Abstract: A beamforming structure is presented which can be used to implement a wide variety of linearly constrained adaptive array processors. The structure is designed for use with arrays which have been time-delay steered such that the desired signal of interest appears approximately in phase at the steered outputs. One major advantage of the new structure is the constraints can be implemented using simple hardware differencing amplifiers. The structure is shown to incorporate algorithms which have been suggested previously for use in adaptive beamforming as well as to include new approaches. It is also particularly useful for studying the effects of steering errors on array performance. Numerical examples illustrating the performance of the structure are presented.
1,879 citations
Book•
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08 Feb 1996
TL;DR: For practicing engineers, researchers, and advanced students in signal processing, Active Noise Control Systems: Algorithms and DSP Implementations will serve as a comprehensive, state-of-the-art text/reference on this important and rapidly changing area of signal processing.
Abstract: From the Publisher:
Active noise control (ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control ANC is achieved by introducing a canceling "anti-noise" wave through an appropriate array of secondary sources When applied accurately, ANC can provide effective solutions to noise-related problems in a broad range of areas, including manufacturing and industrial operations as well as consumer products Consequently, ANC research and development has become an important focus of both industrial applications and engineering research Active Noise Control Systems: Algorithms and DSP Implementations introduces the basic concepts of ANC with an emphasis on digital signal processing (DSP) hardware and adaptive signal processing algorithms, both of which have come into prominence within the last decade The authors emphasize the practical aspects of ANC systems by combining the principles of adaptive signal processing with both experimental results and practical implementation Applications are cited in many fields and encompass all types of noise media, including air-acoustic, hydroacoustic, vibrations, and others The specific implementation stressed is based on the TMS320 family of signal processors from Texas Instruments, which are the most widely used worldwide Coverage of theory includes concise derivations and analyses of commonly used adaptive structures and algorithms for active noise control applications, which are enhanced by the inclusion of a floppy disk featuring C and assembly programs for implementing many ANC systems Mathematical representations are employed and the source code included on the disk is in a form that is easily accessible to anyone using the book For practicing engineers, researchers, and advanced students in signal processing, Active Noise Control Systems: Algorithms and DSP Implementations will serve as a comprehensive, state-of-the-art text/reference on this important and rapidly de
1,561 citations
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TL;DR: In this paper, a residual noise spectrum shaping technique based on the filtered E least-mean-square algorithm has been developed for active noise control of one-dimensional ducts and three-dimensional enclosures, for both narrowband and broadband noises.
Abstract: An active noise control system attenuates the overall sound field. However, in some applications, it is desirable to change the spectral contents of the residual noise. In this Letter, a residual noise spectrum shaping technique based on the filtered‐E least‐mean‐square algorithm has been developed. This technique can be applied to active noise control of one‐dimensional ducts and three‐dimensional enclosures, for both narrow‐band and broadband noises. Computer simulations demonstrate that this method not only attenuates the noise level, but also effectively reshapes the spectrum of the residual noise.
99 citations
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TL;DR: Almost all subjects with bilateral hearing loss exhibited enhanced DLFs near f(e), consistent with cortical reorganisation, while one subject with a high-frequency DR in one ear and good hearing in the other ear showed an enhanced DLF in her better ear.
Abstract: Following a restricted lesion of the cochlea, which produces a "dead region" (DR), animal experiments have revealed an increase in the cortical representation of frequencies just below the edge frequency (f(e)) of the DR. This may result in improved difference limens for frequency (DLFs) just below f(e). In previous studies to assess this, the value of f(e) was not determined precisely. We measured DLFs using human subjects with DRs for whom the values of f(e) had been determined precisely using psychophysical tuning curves. To prevent use of loudness cues, stimuli for the measurement of DLFs had a mean level falling along an equal-loudness contour and levels were roved over a 12-dB range. DLFs were measured for thirteen subjects with a DR in at least one ear. Almost all subjects with bilateral hearing loss exhibited enhanced DLFs near f(e), consistent with cortical reorganisation. This occurred for subjects whose audiograms had both steep and shallow slopes, regardless of hearing aid use, and for two subjects with low-frequency DRs. One subject with a high-frequency DR in one ear and good hearing in the other ear showed an enhanced DLF in her better ear.
41 citations
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TL;DR: An adaptive feedback canceller, which is trained using a set of sparse adaptive algorithms is designed in this paper to take advantage of the sparseness of the acoustic feedback path in a hearing aid.
Abstract: Cancelling the effect of acoustic feedback is a challenging task in the design of a behind the ear digital hearing aid. In traditional behind the ear digital hearing aids, feedback cancellation is usually achieved using an adaptive finite impulse response filter, the weights of which are updated using a suitable learning rule. However, the impulse response of the acoustic feedback path in a hearing aid is sparse in nature and traditional feedback cancellation systems are not designed to utilize this sparseness. An adaptive feedback canceller, which is trained using a set of sparse adaptive algorithms is designed in this paper to take advantage of the sparseness. Further, an attempt has been made to enhance the convergence of the feedback cancellation mechanism by introducing an adaptive de-correlation filter as well as using the concept of probe noise injection. The proposed feedback cancellation schemes are shown to provide improved and accurate feedback cancellation over traditional feedback cancellation mechanisms.
18 citations
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