• 한국소음진동공학회논문집
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• 제21권11호
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• pp.997-1004
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• 2011

A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

• 대한의용생체공학회:의공학회지
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• 제34권4호
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• pp.204-211
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• 2013

In this paper, an algorithm for suppressing acoustic noises contained in stethoscope sound is proposed and implemented in real-time using an embedded DSP system. Sound collected by stethoscope is down-sampled and band-pass filtered, and later an NLMS adaptive filter is used to cancel the acoustic noise induced from external noise sources. Also, the unpredictable impulsive noises due to fabric friction and instantaneous tapping are detected using the SD-ROM algorithm, and suppressed using an algorithm approximating the morphology filter. The proposed algorithm was tested using signals collected with a digital stethoscope mockup, and implemented on an ARM920T-based DSP system.

• 말소리와 음성과학
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• 제4권3호
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• pp.103-110
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• 2012

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. Using the inverse of the eigenvalue-weighted eigen spectra, the algorithm detects the DOAs of multiple sources. To apply the algorithm in target signal detection for GSC-based beamforming, we utilize its spectral response for the DOA of the target source in noisy conditions. The performance of the proposed target signal detection method is compared with those of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics (ROC) curves.

• 한국정보통신학회논문지
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• 제21권7호
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• pp.1342-1348
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• 2017

디지털 정보화 시대에서 영상은 여러 매체에서 필수적으로 이용되며, 잡음은 이러한 영상을 획득, 전송하는 과정에서 여러 외부 원인에 의해 발생된다. 잡음 제거는 영상 처리에서 필수적인 과정이며, 잡음의 종류에는 발생 원인과 형태에 따라 다양한 종류가 있으며 AWGN이 대표적이다. 따라서 본 논문에서는 영상에 첨가된 잡음의 영향을 완화하기 위해, 전처리 과정으로 국부 마스크를 9개의 영역으로 구분하여 각 화소들의 평균을 이용한 에지 검출 방법을 적용한다. 그리고 변형된 에지 검출의 결과에 임계값을 적용하여 국부 마스크에 서로 다른 필터를 적용하는 알고리즘을 제안하였다. 제안한 알고리즘의 우수성을 입증하기 위해, 확대 영상 및 PSNR(peak signal to noise ratio)을 이용하여 기존의 방법들과 그 성능을 비교하였다.

• 한국멀티미디어학회논문지
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• 제8권6호
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• pp.783-789
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• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

• 한국소음진동공학회논문집
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• 제16권1호
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• pp.27-33
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• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.

• 한국음향학회지
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• 제20권7호
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• pp.69-75
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• 2001

화자확인에서 화자내 변이, 잡음환경, 그리고 학습환경과 인식 환경의 불일치는 화자확인 시스템이 실용화될 수 없는 가장 큰 원인이다. 본 연구에서는, 실제 환경에 강인한 화자 확인 시스템의 구현에 초점을 맞추어 음성 전처리 과정인 잡음환경에 강인한 끝점추출 알고리즘, 잡음제거 및 마이크특성 보상기법, LPG(Linear Predictive Coefficient)켑스트럼 가중치에 의한 화자간 변별력 향상 기법을 제안한다. 실험 결과, LPC잔차신호(residue)를 이용한 끝점추출 알고리즘을 사용한 경우 약 17.65% 가량의 끝점 추출 에러율을 향상시켰으며, 제안한 잡음제거 및 마이크특성 보상기법을 사용한 경우 다른 마이크 환경에서 화자 오인식율이 약 36.93% 가량 개선되었다. 또한, 제안한 LPC켑스트럼 가중치에 의한 화자간 변별력 향상 기법은 평균 화자 오인식율을 약 6.515% 향상시켰다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2023년도 춘계학술대회
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• pp.252-253
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• 2023

Container terminal automation might offer many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A robust lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure lane positioning robustness. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions and tested the robustness of the lane detection method with stochastic noise.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.367-368
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• 2007

In this paper, we propose a new de-noising algorithm for 2 dimensional image using discrete wavelet transform. The proposed algorithm consists of edge detection in spatial domain, zero-tree estimation, subband estimation, and shrinkage algorithm. The results from it shows that the denoised image which Is damaged by 20% gaussian noise has 28dB quality for the original one.

• ETRI Journal
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• 제35권3호
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• pp.371-377
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• 2013

An effective signal detection algorithm with low complexity is presented for multiple-input multiple-output orthogonal frequency division multiplexing systems. The proposed technique, QR-MLD, combines the conventional maximum likelihood detection (MLD) algorithm and the QR algorithm, resulting in much lower complexity compared to MLD. The proposed technique is compared with a similar algorithm, showing that the complexity of the proposed technique with T=1 is a 95% improvement over that of MLD, at the expense of about a 2-dB signal-to-noise-ratio (SNR) degradation for a bit error rate (BER) of $10^{-3}$. Additionally, with T=2, the proposed technique reduces the complexity by 73% for multiplications and 80% for additions and enhances the SNR performance about 1 dB for a BER of $10^{-3}$.