• 제목/요약/키워드: Noise detection algorithm

검색결과 873건 처리시간 0.037초

태양광 직렬 아크 검출기의 오검출 방지를 위한 DWT 기반 파라미터 및 반복 알고리즘 (DWT-Based Parameter and Iteration Algorithm for Preventing Arc False Detection in PV DC Arc Fault Detector)

  • 안재범;이진한;이진;류홍제
    • 전력전자학회논문지
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    • 제27권2호
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    • pp.100-105
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    • 2022
  • This paper applies the arc detection algorithm to prevent the false detection in photo voltaic series arc detection circuit, which is required not only to detect the series arc quickly, but also not falsely detect the arc for the non-arc noise. For this purpose, this study proposes a rapid and preventive false detection method of single peak noise and short noise signals. First, to prevent false detection by single peak noise, Discrete wavelet transform (DWT)-based characteristic parameters are applied to determine the shape and the amplitude of the noise. In addition, arc fault detection within a few milliseconds is performed with the DWT iterative algorithm to quickly prevent false detection for short noise signals, considering the continuity of serial arc noise. Thus, the method operates not only to detect series arc, but also to avoid false arc detection for peak and short noises. The proposed algorithm is applied to real-time serial arc detection circuit based on the TMS320F28335 DSP. The serial arc detection and peak noise filtering performances are verified in the built simulated arc test facility. Furthermore, the filtering performance of short noise generated through DC switch operation is confirmed.

Application of Genetic Algorithm for Large-Scale Multiuser MIMO Detection with Non-Gaussian Noise

  • Ran, Rong
    • Journal of information and communication convergence engineering
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    • 제20권2호
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    • pp.73-78
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    • 2022
  • Based on experimental measurements conducted on many different practical wireless communication systems, ambient noise has been shown to be decidedly non-Gaussian owing to impulsive phenomena. However, most multiuser detection techniques proposed thus far have considered Gaussian noise only. They may therefore suffer from a considerable performance loss in the presence of impulsive ambient noise. In this paper, we consider a large-scale multiuser multiple-input multiple-output system in the presence of non-Gaussian noise and propose a genetic algorithm (GA) based detector for large-dimensional multiuser signal detection. The proposed algorithm is more robust than linear multi-user detectors for non-Gaussian noise because it uses a multi-directional search to manipulate and maintain a population of potential solutions. Meanwhile, the proposed GA-based algorithm has a comparable complexity because it does not require any complicated computations (e.g., a matrix inverse or derivation). The simulation results show that the GA offers a performance gain over the linear minimum mean square error algorithm for both non-Gaussian and Gaussian noise.

휴대용 심전도 측정장치를 위한 실시간 QRS-complex 검출 알고리즘 개발 (Development of Real-time QRS-complex Detection Algorithm for Portable ECG Measurement Device)

  • 안휘;심형진;박재순;임종태;정연호
    • 대한의용생체공학회:의공학회지
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    • 제43권4호
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    • pp.280-289
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    • 2022
  • In this paper, we present a QRS-complex detection algorithm to calculate an accurate heartbeat and clearly recognize irregular rhythm from ECG signals. The conventional Pan-Tompkins algorithm brings false QRS detection in the derivative when QRS and noise signals have similar instant variation. The proposed algorithm uses amplitude differences in 7 adjacent samples to detect QRS-complex which has the highest amplitude variation. The calculated amplitude is cubed to dominate QRS-complex and the moving average method is applied to diminish the noise signal's amplitude. Finally, a decision rule with a threshold value is applied to detect accurate QRS-complex. The calculated signals with Pan-Tompkins and proposed algorithms were compared by signal-to-noise ratio to evaluate the noise reduction degree. QRS-complex detection performance was confirmed by sensitivity and the positive predictive value(PPV). Normal ECG, muscle noise ECG, PVC, and atrial fibrillation signals were achieved which were measured from an ECG simulator. The signal-to-noise ratio difference between Pan-Tompkins and the proposed algorithm were 8.1, 8.5, 9.6, and 4.7, respectively. All ratio of the proposed algorithm is higher than the Pan-Tompkins values. It indicates that the proposed algorithm is more robust to noise than the Pan-Tompkins algorithm. The Pan-Tompkins algorithm and the proposed algorithm showed similar sensitivity and PPV at most waveforms. However, with a noisy atrial fibrillation signal, the PPV for QRS-complex has different values, 42% for the Pan-Tompkins algorithm and 100% for the proposed algorithm. It means that the proposed algorithm has superiority for QRS-complex detection in a noisy environment.

A Pacemaker AutoSense Algorithm with Dual Thresholds

  • Kim, Jung-Kuk;Huh, Woong
    • 대한의용생체공학회:의공학회지
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    • 제23권6호
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    • pp.477-484
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    • 2002
  • A pacemaker autosense algorithm with dual thresholds. one for noise or tachyarrhythmia detection (noise threshold, NT) and the other for intrinsic beat detection (sensing threshold. ST), was developed to improve the sensing performance in single pass VDD electrograms. unipolar electrograms, or atrial fibrillation detection. When a deflection in an electrogram exceeds the NT (defined as 50% of 57), the autosense algorithm with dual thresholds checks if the deflection also exceeds the ST. If it does, the autosense algorithm calculates the signal to noise ratio (SNR) of the deflection to the highest deflection detected by NT but lower than ST during the last cardiac cycle. If the SNR 2, the autosense algorithm declares an intrinsic beat detection and calculates the next ST based on the three most recent intrinsic peaks. If the SNR $\geq$2, the autosense algorithm checks the number of deflections detected by NT during the last cardiac cycle in order to determine if it is a noise detection or tachyarrhythmia detection. Usually the autosense algorithm tries to set the 57 at 37.5% of the average of the three intrinsic beats, although it changes the percentage according to event classifications. The autosense algorithm was tested through computer simulation of atrial electrograms from 5 patients obtained during EP study, to simulate a worst sensing situation. The result showed that the ST levels for autosense algorithm tracked the electrogram amplitudes properly, providing more noise immunity whenever necessary. Also, the autosense algorithm with dual thresholds achieved sensing performance as good as the conventional fixed sensitivity method that was optimized retrospectively.

Efficient Multi-Touch Detection Algorithm for Large Touch Screen Panels

  • Mohamed, Mohamed G.A.;Cho, Tae-Won;Kim, HyungWon
    • IEIE Transactions on Smart Processing and Computing
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    • 제3권4호
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    • pp.246-250
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    • 2014
  • Large mutual capacitance touch screen panels (TSP) are susceptible to display and ambient noise. This paper presents a multi-touch detection algorithm using an efficient noise compensation technique for large mutual capacitance TSPs. The sources of noise are presented and analyzed. The algorithm includes the steps to overcome each source of noise. The algorithm begins with a calibration technique to overcome the TSP mutual capacitance variation. The algorithm also overcomes the shadow effect of a hand close to TSP and mutual capacitance variation by dynamic threshold calculations. Time and space filters are also used to filter out ambient noise. The experimental results were used to determine the system parameters to achieve the best performance.

랜덤 임펄스 잡음제거를 위한 캐스케이드 필터 알고리즘에 관한 연구 (A Study on Cascade Filter Algorithm for Random Valued Impulse Noise Elimination)

  • ;김남호
    • 한국정보통신학회논문지
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    • 제16권3호
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    • pp.598-604
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    • 2012
  • 영상신호는 신호를 처리하는 과정에서 다양한 잡음에 의해 훼손되어지며, 이러한 신호를 복원하기 위한 많은 연구가 이루어지고 있다. 본 논문에서는 랜덤 임펄스 잡음을 제거하기 위한 캐스케이드 필터 알고리즘을 제안하였다. 알고리즘은 잡음검출과 잡음제거 등 두 과정으로 구성되었으며, 잡음검출을 위하여 마스크의 분산과 중앙화소에 의한 분산을 이용하였다. 또한, 잡음신호에 대해서 스위칭 self adaptive weighted median 필터로 처리한 후, 변형된 가중치 알고리즘을 적용하여 제거하였다. 제안한 알고리즘은 잡음신호만을 제거하고 비잡음신호는 그대로 보존하여, 우수한 에지 보존특성 및 잡음제거 능력을 나타내었다.

자동차 잡음 환경에서 웨이브렛 밴드 엔트로피 앙상블 분석을 이용한 음성구간 검출 알고리즘 (Voice Activity Detection Algorithm using Wavelet Band Entropy Ensemble Analysis in Car Noisy Environments)

  • 이기현;이윤정;김명남
    • 한국멀티미디어학회논문지
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    • 제16권9호
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    • pp.1005-1017
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    • 2013
  • 음성구간 검출은 음성과 잡음이 섞인 신호에서 음성구간과 비음성구간을 구분하는 과정으로 음성 향상을 위한 신호처리에서 매우 중요한 과정이다. 지금까지 음성구간 검출에 관한 많은 연구가 있었지만, 낮은 신호 대 잡음비 환경이나 자동차 잡음과 같은 시간에 따른 변화가 심한 잡음환경에서는 좋은 성능을 보이지 못하였다. 본 논문에서는 웨이브렛 밴드 엔트로피 기반의 앙상블 분산과 소프트 문턱치 기법을 이용한 새로운 음성구간 검출 알고리듬을 제안하였다. 제안한 알고리듬의 성능을 비교 평가하기 위하여 자동차 잡음이 있는 다양한 신호 대 잡음비 환경에서 실험을 수행하였으며 실험결과, 제안한 방법의 우수한 성능을 확인할 수 있었다.

웨이블렛을 이용한 지중송전계통 고장검출 및 노이즈 제거 알고리즘 개발 (Development of Fault Detection and Noise Cancellation Algorithm Using Wavelet Transform on Underground Power Cable Systems)

  • 정채균;이종범
    • 전기학회논문지
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    • 제56권7호
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    • pp.1191-1198
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    • 2007
  • In this paper, the fault detection and noise cancellation algorithm based on wavelet transform was developed to locate the fault more accurately. Specially, noise cancellation algorithm was based on the correlation of wavelet coefficients at multi-scales. Fault detection, classification and location algorithm were tested by EMTP simulation on real power cable system. From these results, the faults can be detected and located even in very difficult situations, such as at different inception angle and fault resistance.

Wavelet을 이용한 사용자 적응 동잡음 판단 알고리즘 (User-Adaptive Movement Noise Detection Algorithm Using Wavelet Transform)

  • 반다희;권성오
    • 한국통신학회논문지
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    • 제40권6호
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    • pp.1120-1129
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    • 2015
  • 본 논문은 심박에 동기화된 맥파 즉 PPG신호를 측정하고, 신호에 동잡음이 포함 되어있는지를 판단하는 방안을 제안한다. 피 측정자의 움직임에 의한 동잡음은 PPG신호를 심각하게 왜곡한다. 따라서 신호에 동잡음이 포함되었는지 판단하는 신호처리 방법이 요구된다. 본 논문에서는 측정하는 PPG신호에 동잡음이 포함되어있는지를 판단하기 위해 국소푸리에변환 대신 웨이블릿 변환을 이용하여 결정하는 신호처리 방법을 제안한다. 또한, 다양한 웨이블릿 중에서 피실험자의 PPG 신호에 적응된 웨이블릿 선택하였다. 실험에서 사용자가 측정 전체 시간 대비 20%, 30% 시간동안 임의의 움직임을 통해 동잡음을 포함시킨 경우 제안한 신호처리 방법을 이용한 결과 사용자가 동잡음을 포함시킨 모든 구간을 동잡음이 포함된 구간으로 판단하였으며, 고정 웨이블릿 방법보다 더 우수한 성능을 보였다.

Mean Shift 알고리즘과 Canny 알고리즘을 이용한 에지 검출 향상 (Using mean shift and self adaptive Canny algorithm enhance edge detection effect)

  • ;신성윤;이양원
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2008년도 제39차 동계학술발표논문집 16권2호
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    • pp.207-210
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    • 2009
  • Edge detection is an important process in low level image processing. But many proposed methods for edge detection are not very robust to the image noise and are not flexible for different images. To solve the both problems, an algorithm is proposed which eliminate the noise by mean shift algorithm in advance, and then adaptively determine the double thresholds based on gradient histogram and minimum interclass variance, With this algorithm, it can fade out almost all the sensitive noise and calculate the both thresholds for different images without necessity to setup any parameter artificially, and choose edge pixels by fuzzy algorithm.

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