• Nuclear Engineering and Technology
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• 제51권3호
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• pp.719-722
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• 2019

Gamma-ray images generally suffer from a lot of noise because of low photon detection in the gamma camera system. The purpose of this study is to improve the image quality in gamma-ray images using a gamma camera system with a fast nonlocal means (FNLM) noise reduction algorithm with an acceleration function. The designed FNLM algorithm is based on local region considerations, including the Euclidean distance in the gamma-ray image and use of the encoded information. To evaluate the noise characteristics, the normalized noise power spectrum (NNPS), contrast-to-noise ratio (CNR), and coefficient of variation (COV) were used. According to the NNPS result, the lowest values can be obtained using the FNLM noise reduction algorithm. In addition, when the conventional methods and the FNLM noise reduction algorithm were compared, the average CNR and COV using the proposed algorithm were approximately 2.23 and 7.95 times better than those of the noisy image, respectively. In particular, the image-processing time of the FNLM noise reduction algorithm can achieve the fastest time compared with conventional noise reduction methods. The results of the image qualities related to noise characteristics demonstrated the superiority of the proposed FNLM noise reduction algorithm in a gamma camera system.

• 한국ITS학회 논문지
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• 제11권1호
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• pp.86-91
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• 2012

다양한 잡음환경에 노출되는 텔레메틱스 기반의 음성 통화 시스템에서 고품질의 통화 품질을 제공하기 위해서는 저연산량을 가지며 효과적으로 배경 잡음을 제거할 수 있는 잡음제거 알고리즘이 요구된다. 본 논문에서는 Mel-Filter 기반의 잡음제거 알고리즘을 제안하며, 제안된 알고리즘을 기존 잡음제거 알고리즘들과 비교하여 설명한다. 자동차 잡음과 배블 잡음 환경에서 잡음제거 알고리즘의 성능 측정 결과, 제안된 Mel-Filter 기반의 잡음제거 알고리즘이 기존 잡음제거 알고리즘들에 비해 비슷한 PESQ 성능에 적은 연산량을 가지는 장점을 가지고 있으며, 제안된 잡음제거 알고리즘이 텔레메틱스 단말기에서 효과적으로 잡음을 제거할 수 있음을 입증하였다.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.748-764
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• 2019

In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.1016-1019
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• 2004

The study of the noise reduction of an automobile has been concentrated on the reduction of the automotive engine noise because the engine noise is the major cause of automotive noise. However, many studies of automotive engine noise led to the interest of the noise reduction of the exhaust and intake system. The method of the reduction of the induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to this problem, the modified FXLMS algorithm using Moving Bandpass Filter was proposed. In this study, MBPF was implemented and use ANC for automotive intake under revived rapidly accelerated driving conditions and it was verified its performance.

• 한국자동차공학회논문집
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• 제11권6호
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• pp.183-189
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• 2003

The study of the automotive noise reduction has been concentrated on the reduction of the automotive engine noise because the engine noise is the major cause of automotive noise. However, many studies of automotive engine noise led to the interest of the noise reduction of the exhaust and intake system. Recently, the active control method is used to reduce the noise of an automotive exhaust and intake system. It is mostly used the LMS(Least-Mean-Square) algorithm as an algorithm of active control because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an Active Noise Control system. However, the convergence performance of LMS algorithm went bad when the FXLMS algorithm was applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to solve this problem, the modified FXLMS algorithm is proposed. In this study, the improvement of the control performance using the modified FXLMS algorithm under rapidly and suddenly accelerated driving conditions was identified. Also, the performance of an active control using the LMS algorithm under rapidly accelerated driving conditions was evaluated through the theoretical derivation using a chirp signal to have similar characteristics with the induction noise signal.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.780-783
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• 2004

Recently Intake noise has been extensively studied to reduce the engine noise. In order to diminish intake noise several resonators were added to the intake system. However this can cause a reduction of engine output power and an increase of fuel consumption. In this study, active noise control simulation of the Filtered-x LMS algorithm is applied real instrumentation intake noise data under rapid acceleration because intake noise is more excessively increased under the such a harsh condition. But the FXLMS algorithm has poor control performance when the system is disturbed. Thus modified FXLMS algorithm using L-point running average filter is developed to improve the control performance under the rapid acceleration and disturbance. The noise reduction quantity of modified Filtered-x LMS algorithm is more than original one in two cases. In the case of control for real instrumentation intake noise data, maximum residual noise of modified FXLMS algorithm is 2.5 times less than applied the FXLMS and also in the case of disturbed, the modified FXLMS algorithm shows excellent control performance but FXLMS algorithm cat not control.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.57-60
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• 2003

We have proposed the adaptive noise reduction algorithm using the MDFT. The algorithm proposed use the linear prediction coefficients of the AR method based on Sign algorithm that is the modified LMS instead of the least mean square(LMS). The signals with a random noise tracking performance are examined through computer simulations and confirmed that the high speed adaptive noise reduction processing system is realized with rapid convergence.

• 한국컴퓨터정보학회논문지
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• 제17권8호
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• pp.91-97
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• 2012

본 논문에서는 각 프레임에서의 음성신호 및 비음성신호 구간을 검출하는 음성인식 알고리즘을 제안한다. 그리고 음성신호 및 비음성신호 구간의 검출에 따라서 각 프레임에서 잡음을 제거하는 멀티밴드필터에 의한 환경잡음억압 알고리즘을 제안한다. 이 알고리즘은 음성으로부터 특징 파라미터를 추출하여 필터뱅크의 서브밴드 영역에서 잡음을 제거하는 방법이다. 본 실험에서는 환경잡음억압 알고리즘의 성능을 멀티밴드필터를 사용하여 각 프레임에서 잡음을 제거하는 실험결과를 나타낸다. 잡음에 의하여 오염된 음성에 대하여 스펙트럴 왜곡률을 사용하여 본 알고리즘이 유효하다는 것을 확인한다.

• 전기학회논문지
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• 제60권1호
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• pp.201-204
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• 2011

For efficient noise reduction in a Fourier transform ion cyclotron resonance (FT-ICR) mass spectrum, a new algorithm was proposed. The suggested algorithm reduces white and electrical noise, and it improves signal-to-noise ratio. This algorithm has been optimized to reduce the noise more efficiently using the traces of signal level. The algorithm has been efficiently combined with derivative window to improve the resolution as well S/N. Time domain data was corrected for DC voltage interference. $t^n$ window was applied in time domain data to improved the resolution. However, $t^n$ window can improve the signal resolution, it will also increase the noise level in frequency domain. Therefore, newly developed noise reduction algorithm will be applied to make a balance between resolving power and S/N ratio for magnitude mode. The trace algorithm can determine the current data point with several data points (mean, past data, calculated past data). In the current calculations, we assumed data points with S/N ratio more than 3 were considered as signal data points. After the windowing and noise reduction, both resolution and signal-to-noise ratio were improved. This algorithm is applicable more efficiently to frequency dependent noise and large size data.

• 전기학회논문지P
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• 제62권3호
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• pp.111-116
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• 2013

Noise problem that occurs on the road is raising a lot of problems in the economic, social and environmental aspects. The objective of this paper is to propose ANC(active noise cancellation)-based road traffic noise reduction algorithm-model which can reduce noise by generating frequency opposed to noise sources to improve and complement the problem that existing physical form of a noise barrier. In this paper, we measured the noise characteristic from collection of two difference car noise also ANC simulation has been performed by using road traffic noises input. In order to compare the control performance, we performed noise reduction simulation of ANC by filtered-X LMS algorithm and delayed control signal injection. As a result of this simulation, we confirmed that convergence performance and noise decrease effect to the filtered-X LMS algorithm by inputting the road traffic noise.