• 제목/요약/키워드: adaptive detection

검색결과 1,033건 처리시간 0.027초

페이딩 채널에서 직렬 결합 CPM (SCCPM)에 대한 RS-A-SISO 알고리즘과 확률 밀도 진화 분석 (Density Evolution Analysis of RS-A-SISO Algorithms for Serially Concatenated CPM over Fading Channels)

  • 정규혁;허준
    • 대한전자공학회논문지TC
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    • 제42권7호
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    • pp.27-34
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    • 2005
  • Iterative detection은 additive white Gaussian noise(AWGN) channel의 경우 interleaver들을 포함한 조합유한상태머신(concatenated Finite State Machine)들에 대해 근사적으로 optimal solution에 가깝다는 것이 입증되었습니다. 수신단에서 정확한 채널 상태 정보(perfect channel state information)가 얻어질 수 없는 경우 adaptive Iterative detection이 시간적으로 변하거나 또는 부정확한 채널 변수를 다루기위해 필요합니다. Iterative detection과 adaptive iterative detection대한 기본 building block은 각각 Soft-Input Soft-Output (SISO)와adaptive SISO (A-SISO)입니다. SISO와 A-SISO의 complexity은 state memory나 channel memory에 비례해서 지수적으로 증가합니다. 본 논문에서는 Reduced State SISO (RS-SISO) 알고리즘이 A-SISO의 complexity 감소를 위해 적용되어 fading ISI channel을 통한 serially concatenated CPM의 성능이 adaptive iterative detection을 이용하면 터보 코드 같은 성능을 나타내는 것과 또한 RS-A-SISO system이 큰 iterative detection gain을 가지는 것을 보였습니다. RS-A-SISO 알고리즘에 대한 다양한 design option들의 성능을 평가하였으며 성능과 complexity를 비교하였습니다. 또한 보통 AWGN 채널에서 사용되어지는 density evolution 분석기법이 주파수 선택적인 페이딩 채널에서 RS-A-SISO 시스템에서도 좋은 분석기법임을 보였습니다

열처리 환경에서 웨이브렛 적응 필터를 이용한 초음파 비파괴 검사의 결함 검출 (Flaw Detection of Ultrasonic NDT in Heat Treated Environment Using WLMS Adaptive Filter)

  • 임내묵;전창익;김성환
    • 한국음향학회지
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    • 제18권7호
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    • pp.45-55
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    • 1999
  • 본 논문에서는 그레인 잡음을 제거하기 위해서 웨이브렛 변환(wavelet transform)에 근간을 둔 웨이브렛 적응 필터(WLMS adaptive filter : Wavelet domain Least Mean Square adaptive filter)를 사용하였다. 보통 그레인 잡음은 고온의 환경에서 금속의 결정구조가 변화함에 따라 발생된다. 웨이브렛 평면에서의 적응 필터링은 필터의 입력신호를 직교 변환하여 입력으로 이용함으로써 수렴 속도를 향상시킬 수 있는 장점을 가지고 있다. 적응 필터의 기준 입력 신호는 원시 입력 신호를 지연시킨 신호를 이용하였으며, 적응 필터의 출력은 다시 CA-CFAR(Cell Average - Constant False Alarm Rate) 임계 추정기(threshold estimator)를 거쳐 자동적으로 원하는 신호부분만 나타내도록 하였다. 우선 신호의 통계적 특성을 알기 위하여 run 테스트를 수행하여 기준 입력 신호가 비정상성(nonstationarity)을 나타냄을 보였고, 웨이브렛 적응필터가 시평면 적응필터보다 수렴속도면에서 우수함을 보였으며, 각 적응 필터의 출력신호에 대해서 신호대 잡음비를 통해 성능평가를 하였다. 시평면 적응 필터링 후에는 신호대 잡음비가 2-3㏈ 향상을 보였고, 반면 웨이브렛 적응 필터링후에는 신호대 잡음비가 4-6㏈ 향상을 보였다.

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성상도 집합 그룹핑 기반의 적응형 병렬 및 반복적 QRDM 검출 알고리즘 (Adaptive Parallel and Iterative QRDM Detection Algorithms based on the Constellation Set Grouping)

  • 마나르모하이센;안홍선;장경희;구본태;백영석
    • 한국통신학회논문지
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    • 제35권2A호
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    • pp.112-120
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    • 2010
  • 본 논문에서는 집합 그룹핑을 이용한 APQRDM (adaptive parallel QRDM) 알고리즘과 AIQRDM (adaptive iterative QRDM) 알고리즘을 제안한다. 제안된 검출 알고리즘은 집합 그룹핑을 이용하여 QRDM 알고리즘의 트리 검색 단계를 PDP (partial detection phases) 로 분할하여 수행한다. 기존 QRDM 알고리즘의 트리 검색 단계가 4개의 PDP로 나누어질 때, APQRDM 알고리즘은 기존 QRDM 알고리즘의 1/4 에 해당하는 검출 지연(latency) 을 가지며, AIQRDM 알고리즘은 기존 QRDM 알고리즘의 약 1/4에 해당하는 하드웨어 요구량을 가진다. 모의실험 결과는 $4{\times}4$ 시스템의 경우, APQRDM 알고리즘은 12dB의 Eb/N0에서 기존 QRDM 알고리즘의 약 43%에 해당하는 연산 복잡도를 가지며, AIQRDM 알고리즘은 0dB의 Eb/N0에서 기존 QRDM 알고리즘의 54%, AQRDM 알고리즘의 10%에 해당하는 연산 복잡도를 가짐을 보인다.

자가적응모듈과 퍼지인식도가 적용된 하이브리드 침입시도탐지모델 (An Hybrid Probe Detection Model using FCM and Self-Adaptive Module)

  • 이세열
    • 디지털산업정보학회논문지
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    • 제13권3호
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    • pp.19-25
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    • 2017
  • Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.

적응적 이진화를 이용하여 빛의 변화에 강인한 영상거리계를 통한 위치 추정 (Robust Visual Odometry System for Illumination Variations Using Adaptive Thresholding)

  • 황요섭;유호윤;이장명
    • 제어로봇시스템학회논문지
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    • 제22권9호
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    • pp.738-744
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    • 2016
  • In this paper, a robust visual odometry system has been proposed and implemented in an environment with dynamic illumination. Visual odometry is based on stereo images to estimate the distance to an object. It is very difficult to realize a highly accurate and stable estimation because image quality is highly dependent on the illumination, which is a major disadvantage of visual odometry. Therefore, in order to solve the problem of low performance during the feature detection phase that is caused by illumination variations, it is suggested to determine an optimal threshold value in the image binarization and to use an adaptive threshold value for feature detection. A feature point direction and a magnitude of the motion vector that is not uniform are utilized as the features. The performance of feature detection has been improved by the RANSAC algorithm. As a result, the position of a mobile robot has been estimated using the feature points. The experimental results demonstrated that the proposed approach has superior performance against illumination variations.

Salient Object Detection via Adaptive Region Merging

  • Zhou, Jingbo;Zhai, Jiyou;Ren, Yongfeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4386-4404
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    • 2016
  • Most existing salient object detection algorithms commonly employed segmentation techniques to eliminate background noise and reduce computation by treating each segment as a processing unit. However, individual small segments provide little information about global contents. Such schemes have limited capability on modeling global perceptual phenomena. In this paper, a novel salient object detection algorithm is proposed based on region merging. An adaptive-based merging scheme is developed to reassemble regions based on their color dissimilarities. The merging strategy can be described as that a region R is merged with its adjacent region Q if Q has the lowest dissimilarity with Q among all Q's adjacent regions. To guide the merging process, superpixels that located at the boundary of the image are treated as the seeds. However, it is possible for a boundary in the input image to be occupied by the foreground object. To avoid this case, we optimize the boundary influences by locating and eliminating erroneous boundaries before the region merging. We show that even though three simple region saliency measurements are adopted for each region, encouraging performance can be obtained. Experiments on four benchmark datasets including MSRA-B, SOD, SED and iCoSeg show the proposed method results in uniform object enhancement and achieve state-of-the-art performance by comparing with nine existing methods.

선형레이저빔의 적응적 패턴 분할을 이용한 3차원 표면형상 측정 장치의 성능 향상에 관한 연구 (A Study on the Performance Improvement of a 3-D Shape Measuring System Using Adaptive Pattern Clustering of Line-Shaped Laser Light)

  • 박승규;백성훈;김대규;장원석;이일근;김철중
    • 한국정밀공학회지
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    • 제17권10호
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    • pp.119-124
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    • 2000
  • One of the main problems in 3D shape measuring systems that use the triangulation of line-shaped laser light is precise center line detection of line-shaped laser stripe. The intensity of a line-shaped laser light stripe on the CCD image varies following to the reflection angles, colors and shapes of objects. In this paper, a new center line detection algorithm to compensate the local intensity variation on a line-shaped laser light stripe is proposed. The 3-D surface shape measuring system using the proposed center line detection algorithm can measure 3-D surface shape with enhanced measurement resolution by using the dynamic shape reconstruction with adaptive pattern clustering of the line-shaped laser light. This proposed 3-D shape measuring system can be easily applied to practical situations of measuring 3-D surface by virtue of high speed measurement and compact hardware compositions.

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Adaptive Switching Median Filter for Impulse Noise Removal Based on Support Vector Machines

  • Lee, Dae-Geun;Park, Min-Jae;Kim, Jeong-Ok;Kim, Do-Yoon;Kim, Dong-Wook;Lim, Dong-Hoon
    • Communications for Statistical Applications and Methods
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    • 제18권6호
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    • pp.871-886
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    • 2011
  • This paper proposes a powerful SVM-ASM filter, the adaptive switching median(ASM) filter based on support vector machines(SVMs), to effectively reduce impulse noise in corrupted images while preserving image details and features. The proposed SVM-ASM filter is composed of two stages: SVM impulse detection and ASM filtering. SVM impulse detection determines whether the pixels are corrupted by noise or not according to an optimal discrimination function. ASM filtering implements the image filtering with a variable window size to effectively remove the noisy pixels determined by the SVM impulse detection. Experimental results show that the SVM-ASM filter performs significantly better than many other existing filters for denoising impulse noise even in highly corrupted images with regard to noise suppression and detail preservation. The SVM-ASM filter is also extremely robust with respect to various test images and various percentages of image noise.

Speed and Current Sensor Fault Detection and Isolation Based on Adaptive Observers for IM Drives

  • Yu, Yong;Wang, Ziyuan;Xu, Dianguo;Zhou, Tao;Xu, Rong
    • Journal of Power Electronics
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    • 제14권5호
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    • pp.967-979
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    • 2014
  • This paper focuses on speed and current sensor fault detection and isolation (FDI) for induction motor (IM) drives. A new, accurate and high-efficiency FDI approach is proposed so that a system can continue operating with good performance even in the presence of speed sensor faults, current sensor faults or both. The proposed three paralleled adaptive observers are capable of current sensor fault detection and localization. By using observers, the rotor flux and rotor speed can be estimated which allows the system to run under the speed sensorless vector control mode when a speed sensor fault occurs. In order to detect speed sensor faults, a threshold-based scheme is proposed. To verify the feasibility and effectiveness of the proposed FDI strategy, experiments are carried out under different conditions based on a dSPACE DS1104 induction motor drive platform.

최소자승법을 이용한 적응형 데이터 윈도우의 거리계전 알고리즘 (Distance Relaying Algorithm Based on An Adaptive Data Window Using Least Square Error Method)

  • 정호성;최상열;신명철
    • 대한전기학회논문지:전력기술부문A
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    • 제51권8호
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    • pp.371-378
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    • 2002
  • This paper presents the rapid and accurate algorithm for fault detection and location estimation in the transmission line. This algorithm uses wavelet transform for fault detection and harmonics elimination and utilizes least square error method for fault impedance estimation. Wavelet transform decomposes fault signals into high frequence component Dl and low frequence component A3. The former is used for fault phase detection and fault types classification and the latter is used for harmonics elimination. After fault detection, an adaptive data window technique using LSE estimates fault impedance. It can find a optimal data window length and estimate fault impedance rapidly, because it changes the length according to the fault disturbance. To prove the performance of the algorithm, the authors test relaying signals obtained from EMTP simulation. Test results show that the proposed algorithm estimates fault location within a half cycle after fault irrelevant to fault types and various fault conditions.