• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.91-96
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• 2016

We have surrounded undesired living noises in our life. One of biggest noises coming out of range hood during cooking in the kitchen. A range hood is one of the most important appliances in the kitchen because it ventilates polluted air out during cooking, and maintains air quality in the kitchen. But current kitchen range hoods bring up some issues; First, the range hoods consume massive amount of standby power not in use condition. Second, current models have designed manual fan operating system with sudden onset of noise with starting. In this paper, we propose an auto control system entire processes from air ventilation to noise reduction. Our system is consist of three parts (Eco-sensors pack, Main Controller and Active Noise Controller); Eco-sensors pack detects air pollution of kitchen areas and sends the detection values to Main Controller. Main Controller determines operation of range hood by detected values. Active Noise Controller is located inside of the range hood. It received starting signals from Main Controller which elicits degrees of polluted air condition and fan operating speed from 1 to 3. Once Active Noise Controller detected the signals, it runs a ventilating fan until new value from Main Controller becomes 0. while the range hood works, A noise cancellation algorithm inside of Active Noise Controller become activated to reduce levels of noise. As a result, the proposed system clearly shows reduction in power consumption include standby power and decreases in levels of noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.858-861
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• 2006

In this paper, a study on the noise reduction in a mobile fuel cell system is presented. Among various fuel cell systems around 20W capacities designed for mobile electronic devices, the active direct methanol fuel cell (DMFC) systems have been recently developed. In such systems, the primary noise source is the air pump which provides sufficient air flow ($5{\sim}6$ liter/min) for electrochemical reaction with methanol fuel while the noise contributions from other auxiliary parts are relatively small. Especially, the discrete noise tones generated by the air pump are dominant and those frequency peaks related to the rotor harmonics are needed to be suppressed by a silencer. Therefore. the Herschel/Quinke (HQ) tubes, which use the out-of-phase cancellation of acoustic waves propagating through direct and indirect pathways, are applied to the inlet of the air pump. Performance of noise reduction with HQ silencer is analytically estimated by calculating the transmission. The length and number of thin HQ tubes are optimized to decrease the radiated noise. As a result, the sound pressure level could be successfully reduced by about 10 dB after applying three serially connected HQ tubes.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.238-239
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• 2008

In this paper, active noise control (ANC) of a Volterra system with a nonlinear secondary path is proposed in the presence of a linear acoustic feedback, whereby the conventional ANC of a linear system with online acoustic feedback-path modeling is further extended to ANC of a Volterra system with a linear acoustic feedback path. In particular, the proposed ANC system consists of two adaptive Volterra filters (for nonlinear noise control and nonlinear adaptive noise cancellation) and one feedback-path modeling filter. Simulation results show that the proposed approach yields more effective reduction of disturbances arising from the acoustic feedback, in addition to high nonlinear ANC performance.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.457-460
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• 2005

When a hearing aid' s user is listening through telephone or cellular phone, he/she usually suffers from severe electrical magnetic interference noise. It is because hearing aids amplify voice signal as well as background noise. A telecoil, an induction coil, is a possible solution for the problem. Because a telecoil has the characteristic of high pass filter, it has some problem of resulting increased high frequency noise. For solving this problem, we can use a capacitor connected with the telecoil in parallel. According to capacitance, receiving signal quality may change. In this paper, proper capacitor values for the best sound quality are investigated by experimental work.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.39-44
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• 1996

The performance of two-channel adaptive noise canceller is ofter degraded by the weights perturbation due to the speech signal. In this paper, an adaptive noise canceller employing a speech detector and two adaptation algorithms which are switched according to the speech detector is proposed. When highly correlated speech signal is detected, the tap weights of the adaptive filter are adapted by the sign algorithm. On the other hand, the weights are adapted by the NLMS algorithm when silence is detected or when the characteristics of the noise propagation channel is changed. The employed speech detector utilizes the power ratio of the input and the output of an adaptive linear prediction-error filter. According to the computer simulation, the proposed method yields better performance than conventional ones.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.27-33
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• 2011

For compensation of channel distortion from multipath fading and impulsive noise, a decision feedback equalizer (DFE) algorithm based on minimization of Error entropy (MEE) is proposed. The MEE criterion has not been studied for DFE structures and impulsive noise environments either. By minimizing the error entropy with respect to equalizer weight based on decision feedback structures, the proposed decision feedback algorithm has shown to have superior capability of residual intersymbol interference cancellation in simulation environments with severe multipath and impulsive noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.3
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• pp.259-269
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• 1991

In this paper, power line harmonic noise which is the most serious problem in the secondary power distribution line is eliminated and analyzed using adaptive noise cancellers with two adaptive algorithms, LMS and individual tap LMS(ITLMS) algorithm. To testify the improvement of data transmission characteristics made by the adaptive filter with two adaptive algorithms, BER was measured in DS spread spectrum communication system including the noise canceller.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.758-760
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• 1995

The purpose of noise cancellation is to estimating signals corrupted by additive noise or interference. In this paper, an adaptive noise canceller is built from a Walsh filter with a new adaptive algorithm. The Walsh filter consists of a Walsh function. Since the Walsh functions are either even or odd functions, the covariance matrix in the tap gain adjustment algorithm can be reduced to a simple form. In this paper, minimization of the mean squre error is accomplished by a proposed adaptive algorithm. The conventional adaptation techniques use a fixed time constant convergence factor by trial and error methods. In this paper, a convergence factor is obtained that is tailored for each adaptive filter coefficient and is updated at each block iteration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.429-431
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• 2019

Noise in image processing has a direct effect on the quality of the image, and adversely affects the processing of the system including algorithms such as image segmentation, edge detection, and image recognition. Therefore, noise reduction plays an important role in the preprocessing process. In this paper, we propose an efficient algorithm to remove noise in high density of Salt and Pepper noise. The proposed algorithm removes noise by gradually expanding the filtering mask according to the density of the noise, and shows excellent noise cancellation performance even in a high density region. In order to evaluate the performance of the proposed algorithm, we compared and analyzed the existing method and the proposed algorithm through simulation.