• 제목/요약/키워드: data detection error

검색결과 723건 처리시간 0.026초

FPGA implementation of overhead reduction algorithm for interspersed redundancy bits using EEDC

  • Kim, Hi-Seok
    • 전기전자학회논문지
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    • 제21권2호
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    • pp.130-135
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    • 2017
  • Normally, in data transmission, extra parity bits are added to the input message which were derived from its input and a pre-defined algorithm. The same algorithm is used by the receiver to check the consistency of the delivered information, to determine if it is corrupted or not. It recovers and compares the received information, to provide matching and correcting the corrupted transmitted bits if there is any. This paper aims the following objectives: to use an alternative error detection-correction method, to lessens both the fixed number of the required redundancy bits 'r' in cyclic redundancy checking (CRC) because of the required polynomial generator and the overhead of interspersing the r in Hamming code. The experimental results were synthesized using Xilinx Virtex-5 FPGA and showed a significant increase in both the transmission rate and detection of random errors. Moreover, this proposal can be a better option for detecting and correcting errors.

Spatial Multiplexing Receivers in UWB MIMO Systems based on Prerake Combining

  • An, Jin-Young;Kim, Sang-Choon
    • Journal of information and communication convergence engineering
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    • 제9권4호
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    • pp.385-390
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    • 2011
  • In this paper, various ultra-wideband (UWB) spatial multiplxing (SM) multiple input multiple output (MIMO) receivers based on a prerake diversity combining scheme are discussed and their performance is analyzed. Several UWB MIMO detection approaches such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC), sorted QR decomposition (SQRD), and maximum likelihood (ML) are considered in order to cope with inter-channel interference. The UWB SM systems based on transmitter-side multipath preprocessing and receiver-side MIMO detection can either boost the transmission data rate or offer significant diversity gain and improved BER performance. The error performance and complexity of linear and nonlinear detection algorithms are comparatively studied on a lognormal multipath fading channel.

Pipe Leak Detection System using Wireless Acoustic Sensor Module and Deep Auto-Encoder

  • Yeo, Doyeob;Lee, Giyoung;Lee, Jae-Cheol
    • 한국컴퓨터정보학회논문지
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    • 제25권2호
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    • pp.59-66
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    • 2020
  • 본 논문에서는 저전력 무선 음향센서 모듈을 통한 데이터 수집과 딥 오토인코더를 이용한 데이터 분석을 통해 배관의 누출을 탐지하는 시스템을 제안한다. 데이터 통신량을 줄이기 위해서 푸리에 변환을 통해 음향센서 데이터 양을 약 1/800로 감소시키는 저전력 무선 음향센서 모듈을 구성하였고, 20kHz~100kHz 주파수 신호를 이용하여 가청 주파수 대역에서 발생하는 노이즈에 강인한 누출 탐지 시스템을 설계하였다. 또한, 데이터 양의 감소에도 배관 누출을 정확하게 탐지하도록 딥 오토인코더를 이용한 데이터 분석 기법을 설계하였다. 수치적인 실험을 통해, 본 논문에서 제안한 누출 탐지 시스템이 고주파 대역대의 노이즈가 섞인 환경에서도 99.94%의 높은 정확도와 Type-II error 0%의 높은 성능을 보이는 것을 검증하였다.

추적 시스템을 위한 최적 검출 문턱값 선택 (Optimal selection of detection threshold for tracking systems)

  • 정영헌
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 추계종합학술대회 논문집
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    • pp.1155-1158
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    • 1999
  • In this paper, we consider the optimal control of detection threshold to minimize the conditional mean-square state estimation error for the probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the closed-form optimal detection threshold. This results are very useful for real-time implemenation.

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동기 능력을 보유한 변형된 BCH 부호 (A Modified BCH Code with Synchronization Capability)

  • 심용걸
    • 정보처리학회논문지C
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    • 제11C권1호
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    • pp.109-114
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    • 2004
  • 본 논문에서는 통신 시스템에서 발생하는 에러를 정정 및 검출하기 위한 새로운 부호와 그 복호 방식을 제안하였다. 데이터 0의 런 길이를 제한하고 데이터 1의 최소 밀도를 증가시키기 위하여 (15, 7) BCH 부호를 변형하였으며 전체 패리티 비트를 추가하였다. 제안된 부호는 (16, 7) 블록 부호이며 비트 클럭 신호의 재생 능력과 높은 에러 제어 능력을 가지고 있다. 제안된 부호에서 데이터 0의 런 길이는 7 이하이고, 데이터 1의 밀도는 1/8 이상이며 최소 해밍 거리가 6임을 입증하였다. 제안된 부호를 사용하였을 때의 복호 에러 확률, 에러 검출 확률, 바른 복호 확률을 제시하였다. 기존의 다른 방식들에 비하여 오류 제어 능력이 우수함을 확인할 수 있었다.

Adaptive Video-Dissolve Detection Method Based on Correlation Between Two Scenes

  • Won, Jong-Un;Park, Jae-Gark;Chung, Yoon-su;Park, Kil-Houm
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -3
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    • pp.1519-1522
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    • 2002
  • In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error that is the difference between an ideally modeled dissolve curve without any correlation and an actual variance curve with a correlation. The dissolve modeling error is determined based on a correlation between two scenes and variances for each scene. First, Candidate regions are extracted by using the characteristics of a parabola that is downward convex, then the candidate region will be verified based on a dissolve modeling error. If a dissolve modeling error on a candidate region is less than a threshold that is defined by a dissolve modeling error with a target correlation, the candidate region should be a dissolve region with a correlation less than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed algorithm was tested on various types of data and its performance proved to be more accurate and reliable when compared with other commonly used methods

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Development of a Multiple Linear Regression Model to Analyze Traffic Volume Error Factors in Radar Detectors

  • Kim, Do Hoon;Kim, Eung Cheol
    • 한국측량학회지
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    • 제39권5호
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    • pp.253-263
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    • 2021
  • Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

MIMO 채널 대각화: 선형 검출 ZF, MMSE (MIMO Channel Diagonalization: Linear Detection ZF, MMSE)

  • 양재승;신태철;이문호
    • 한국인터넷방송통신학회논문지
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    • 제16권1호
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    • pp.15-20
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    • 2016
  • 공간다중화 방식을 사용하는 MIMO 시스템은 다이버시티 기법을 사용하는 MIMO 시스템과 비교할 때 높은 전송률을 달성하지만 다이버시티 이득이 낮아 데이터 전송 신뢰도를 높이기 위하여 MIMO 수신단에서 공간정보스트림을 분리해야한다. 본 논문에서는 격자부호에 의한 채널 용량 검출 기법, 사용자 3인인 간섭채널과 선형검출기법인 ZF(Zero Forcing)와 MMSE(Minimum Mean Square Error) 검파 기법을 비교했다. 이때 채널은 Diagonal 채널이 된다. 즉, Diagonal 채널은 $[H]_N[H]_N^{-1}=[I]_N$로 역행렬이 element-wise inverse로 Jacket 행렬의 성질을 만족함을 확인했다.

Developing and Evaluating Deep Learning Algorithms for Object Detection: Key Points for Achieving Superior Model Performance

  • Jang-Hoon Oh;Hyug-Gi Kim;Kyung Mi Lee
    • Korean Journal of Radiology
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    • 제24권7호
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    • pp.698-714
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    • 2023
  • In recent years, artificial intelligence, especially object detection-based deep learning in computer vision, has made significant advancements, driven by the development of computing power and the widespread use of graphic processor units. Object detection-based deep learning techniques have been applied in various fields, including the medical imaging domain, where remarkable achievements have been reported in disease detection. However, the application of deep learning does not always guarantee satisfactory performance, and researchers have been employing trial-and-error to identify the factors contributing to performance degradation and enhance their models. Moreover, due to the black-box problem, the intermediate processes of a deep learning network cannot be comprehended by humans; as a result, identifying problems in a deep learning model that exhibits poor performance can be challenging. This article highlights potential issues that may cause performance degradation at each deep learning step in the medical imaging domain and discusses factors that must be considered to improve the performance of deep learning models. Researchers who wish to begin deep learning research can reduce the required amount of trial-and-error by understanding the issues discussed in this study.

퍼지 알고리즘을 이용한 오류 검출 및 진단에 관한 연구 (A Study on Error Detection and Diagnosis using Fuzzy Algorithm)

  • 유병삼;신두진;허욱열;김진환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 D
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    • pp.2485-2487
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    • 2000
  • In this paper, we use a fuzzy algorithm to detect and diagnose the error which is caused by time delay of the computer-controlled system. Generally, a computer-controlled system is composed of computer and process. And they communicate the data each other. In data communication, error occurs by some reasons, such as noise, disturbance, hardware defect, etc. Time delay is one of the reasons. And time delay makes it difficult to distinguish whether the system really has a problem or not. Therefore, we need to detect and diagnose the error from time delay. For difficulty of modeling and ambiguity of classification, we use a fuzzy algorithm. To verify the better performance of the proposed algorithm, we exemplified by some simulation results.

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