• 제목/요약/키워드: error bound

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Upper Bounds for the Performance of Turbo-Like Codes and Low Density Parity Check Codes

  • Chung, Kyu-Hyuk;Heo, Jun
    • Journal of Communications and Networks
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    • 제10권1호
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    • pp.5-9
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    • 2008
  • Researchers have investigated many upper bound techniques applicable to error probabilities on the maximum likelihood (ML) decoding performance of turbo-like codes and low density parity check (LDPC) codes in recent years for a long codeword block size. This is because it is trivial for a short codeword block size. Previous research efforts, such as the simple bound technique [20] recently proposed, developed upper bounds for LDPC codes and turbo-like codes using ensemble codes or the uniformly interleaved assumption. This assumption bounds the performance averaged over all ensemble codes or all interleavers. Another previous research effort [21] obtained the upper bound of turbo-like code with a particular interleaver using a truncated union bound which requires information of the minimum Hamming distance and the number of codewords with the minimum Hamming distance. However, it gives the reliable bound only in the region of the error floor where the minimum Hamming distance is dominant, i.e., in the region of high signal-to-noise ratios. Therefore, currently an upper bound on ML decoding performance for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix cannot be calculated because of heavy complexity so that only average bounds for ensemble codes can be obtained using a uniform interleaver assumption. In this paper, we propose a new bound technique on ML decoding performance for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix using ML estimated weight distributions and we also show that the practical iterative decoding performance is approximately suboptimal in ML sense because the simulation performance of iterative decoding is worse than the proposed upper bound and no wonder, even worse than ML decoding performance. In order to show this point, we compare the simulation results with the proposed upper bound and previous bounds. The proposed bound technique is based on the simple bound with an approximate weight distribution including several exact smallest distance terms, not with the ensemble distribution or the uniform interleaver assumption. This technique also shows a tighter upper bound than any other previous bound techniques for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix.

선형화 오차에 강인한 확장칼만필터 (An Extended Kalman Filter Robust to Linearization Error)

  • 혼형수;이장규;박찬국
    • 제어로봇시스템학회논문지
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    • 제12권2호
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    • pp.93-100
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    • 2006
  • In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.

M진 위상 천이 변조 심볼 오류 확률의 간단한 하한식 (Simple Lower Bound for MPSK Symbol Error Probability)

  • 윤동원
    • 한국전자파학회논문지
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    • 제11권3호
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    • pp.352-357
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    • 2000
  • 이 논문에서는 동기 MPSK 신호에 대하여 새로운 간단한 심볼 오류 확률 하한식을 유도하고 분석한다. 보통 심볼 오류 확률 유도는 먼저 덧셉꼴 백색 정규잡음(AWGN) 환경에서 유도하고 이에 대한 결과를 바탕으로 여러 페이딩 환경에서의 심볼 오류 확률을 구하는 것이 일반적인 방법이다. 그러나 동기 MPSK의 경우는 여러 페 이딩 환경에서의 오류 확률 식이 구해져 있으나 가장 기본이 되는 덧셈팔 백색 정규 잡음 환경에서는 정확히 closed-form으로 유도하지 못하는 것으로 알려져 있다. 여기서는 먼저 나카가미 페이딩 환경에서 동기 MPSK 신호의 심볼 오류 확률식을 이용하여 나카가미 페이딩 지수가 무한대로 감에 따라 페이딩이 없는 덧셈꼴 백색 정규 잡음 채널로 돌아가는 성질을 이용하여 새로운 근사식을 유도하고 분석한다.

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시화호.인천연안 환경자료의 오차범위 분석 (Error Bounds Analysis of the Environmental Data in Lake Shihwa and Incheon Coastal Zone)

  • 조홍연
    • Ocean and Polar Research
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    • 제30권2호
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    • pp.149-158
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    • 2008
  • The characteristic analysis of the estimated population parameters, i.e., standard deviation and error bound of coastal pollutant concentrations (hereafter PC, i.e., COD, TN, and TP concentrations), was carried out by using environmental data with different sampling frequency in Lake Shihwa and Incheon coastal zone. The results clearly show that standard deviation of the PC increases as its mean value increases. The error bounds of the annual mean values based on seasonally measured DO concentrations and PC data in Incheon coastal zone were estimated as ranges 2.26 mg/l, $0.68{\sim}0.86\;mg/l$, $0.62{\sim}0.80\;mg/l$, and $0.074{\sim}0.082\;mg/l$, respectively. In terms of annual mean of the DO concentration and PC in Lake Shihwa, the error bounds based on monthly measured data from 1997 to 2003 were also estimated as ranges 4.0 mg/l, 3.0 mg/l, $0.5{\sim}1.0\;mg/l$, and 0.05 mg/l, respectively. The error bound on the basis of real-time monitoring data is $7{\sim}13%$ only as compared to that of monthly measured data.

A POSTERIORI ERROR ESTIMATOR FOR LINEAR ELASTICITY BASED ON NONSYMMETRIC STRESS TENSOR APPROXIMATION

  • Kim, Kwang-Yeon
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제16권1호
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    • pp.1-13
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    • 2012
  • In this paper we present an a posteriori error estimator for the stabilized P1 nonconforming finite element method of the linear elasticity problem based on a nonsymmetric H(div)-conforming approximation of the stress tensor in the first-order Raviart-Thomas space. By combining the equilibrated residual method and the hypercircle method, it is shown that the error estimator gives a fully computable upper bound on the actual error. Numerical results are provided to confirm the theory and illustrate the effectiveness of our error estimator.

구성부호의 연접방법에 따른 직렬연접 길쌈부호의 성능 (Performance of Serial Concatenated Convolutional Codes according to the Concatenation Methods of Component Codes)

  • 배상재;이상훈;주언경
    • 한국통신학회논문지
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    • 제27권1A호
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    • pp.18-25
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    • 2002
  • 본 논문에서는 AWGN 채널환경에서 직렬연접 길쌈부호(serial concatenated convolutional codes; SCCC)의 세 가지 형태에 대한 성능을 비교 및 분석한다. 모의실험 결과 낮은 신호 대 잡음비(signal-to-noise ratio; SNR) 영역에서는 첫 번째 형태의 성능이 가장 우수하였다. 그러나 높은 SNR 영역에서는 세 번째 형태의 성능이 가장 우수함을 아 수 있었다. 그리고 첫 번째 형태에서는 SNR과 반복복호 횟수를 증가시키더라도 성능이 더 이상 향상되지 않는 오류마루(error floor)가 발생하였다. 그러나 두 번째와 세 번째 형태는 높은 SNR에서 반복복호를 5회 이상 수행하더라도 성능이 계속 향상되며 오류마루가 나타나지 않았다. 그리고 SNR이 증가할수록 세 가지 직렬연접 길쌈부호의 BER 성능은 각각의 상위경계(upper bound) 성능에 근접해짐을 알 수 있었다. 또한 자유거리(free distance)가 가장 큰 세 번째 직렬연접 길쌈부호가 세 가지 구조 중에서 가장 우수한 상위경계 성능을 나타내었다.

A Study on Particle Filter based on KLD-Resampling for Wireless Patient Tracking

  • Ly-Tu, Nga;Le-Tien, Thuong;Mai, Linh
    • Industrial Engineering and Management Systems
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    • 제16권1호
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    • pp.92-102
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    • 2017
  • In this paper, we consider a typical health care system via the help of Wireless Sensor Network (WSN) for wireless patient tracking. The wireless patient tracking module of this system performs localization out of samples of Received Signal Strength (RSS) variations and tracking through a Particle Filter (PF) for WSN assisted by multiple transmit-power information. We propose a modified PF, Kullback-Leibler Distance (KLD)-resampling PF, to ameliorate the effect of RSS variations by generating a sample set near the high-likelihood region for improving the wireless patient tracking. The key idea of this method is to approximate a discrete distribution with an upper bound error on the KLD for reducing both location error and the number of particles used. To determine this bound error, an optimal algorithm is proposed based on the maximum gap error between the proposal and Sampling Important Resampling (SIR) algorithms. By setting up these values, a number of simulations using the health care system's data sets which contains the real RSSI measurements to evaluate the location error in term of various power levels and density nodes for all methods. Finally, we point out the effect of different power levels vs. different density nodes for the wireless patient tracking.

VALUE FUNCTIONS AND ERROR BOUNDS OF TRUST REGION METHODS

  • Zhao, Wenling;Wang, Changyu
    • Journal of applied mathematics & informatics
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    • 제24권1_2호
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    • pp.245-259
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    • 2007
  • This paper studies some properties of the value functions and gives some sufficient and necessary conditions about the presented global error and local error. And it leads to one kind of relationship between iterative points and optimal solution or K-T point.