• Title/Summary/Keyword: error criterion

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A criterion for selecting sensor outputs in bearing estimation algorithm without eigendecomposition (고유치분해가 필요없는 방위각 추정 알고리듬에서 센서신호의 선택기준)

  • 정대원;박상배;이균경
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.70-75
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    • 1993
  • The performance of the BEWE(Bearing Estimation Without Eigendecomposition) algorithm depends on the sensor outputs which are selected to construct the projection matrix. In this paper, we construct the covariance matrix of the bearing estimates for two targets and propose the criterion to select the sensor outputs which minimize the covariance matrix. The computer simulation conforms that the estimation error is smallest when the sensor outputs are selected based on the proposed criterion.

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An Efficient Iterative Decoding Stop Criterion using the Variance Value of LLR (LLR의 분산값을 이용한 효율적인 반복중단 알고리즘)

  • 심병섭;정대호;정성태;정경택;김환용
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.178-181
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    • 2003
  • In this paper, it proposes the efficient iterative decoding stop criterion using the variance value of LLR. It is verifying that the proposal iterative decoding stop criterion can be reduced the average iterative decoding number compared to conventional schemes with a negligible degradation of the error performance.

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A New Constant Modulus Algorithm based on Maximum Probability Criterion

  • Kim, Nam-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.2A
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    • pp.85-90
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    • 2009
  • In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

An Adaptive Bit-reduced Mean Absolute Difference Criterion for Block-Matching Algorithm and Its VlSI Implementation (블럭 정합 알고리즘을 위한 적응적 비트 축소 MAD 정합 기준과 VLSI 구현)

  • Oh, Hwang-Seok;Baek, Yun-Ju;Lee, Heung-Kyu
    • Journal of KIISE:Software and Applications
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    • v.27 no.5
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    • pp.543-550
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    • 2000
  • An adaptive bit-reduced mean absolute difference (ABRMAD) is presented as a criterion for the block-matching algorithm (BMA) to reduce the complexity of the VLSI Implementation and to improve the processing time. The ABRMAD uses the lower pixel resolution of the significant bits instead of full resolution pixel values to estimate the motion vector (MV) by examining the pixels Ina block. Simulation results show that the 4-bit ABRMAD has competitive mean square error (MSE)results and a half less hardware complexity than the MAD criterion, It has also better characteristics in terms of both MSE performance and hardware complexity than the Minimax criterion and has better MSE performance than the difference pixel counting(DPC), binary block-matching with edge-map(BBME), and bit-plane matching(BPM) with the same number of bits.

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Consideration to the Stability of FLC using The Circle Criterion (Circle Criterion을 이용한 FLC의 안정도에 대한 고찰)

  • Lee, Kyoung-Woong;Choi, Han-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.5
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    • pp.525-529
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    • 2009
  • Most of FLC received input data from error e and change-of-error e' with no relation with system complexity. Basic scheme follows typical PD and PI or PID Controller and that has been developed through fixed ME In this paper, We studied the relationship between MF and system response and system response through changing Fuzzy variable of consequence MF and propose the simple FLC using this relationship. The response of FLC is changed according to the width of Fuzzy variable of consequence MF. As changing the Fuzzy variable of consequence MF shows various nonlinear characteristic, we studied the relation between response and MF using analytical method. We designed the effective FLC using three-variable MF and nine rules and took simulation for verification. In this study, we propose the method to design system with FLC in stability point which is an impotent characteristic of designing system. The circle criterion which is adapted to analysis the nonlinear system is put to use for proposed method. Since SISO FLC has a time-invariant and odd characteristic we can use the critical point not disk which is generally used to determine the stability in the circle criterion, to determine the stability. Using this, we can get the maximum critical point plot of SISO FLC with changing the consequence fuzzy variables. The predetermined critical point plot of FLC can be used to decide the region of the system to be stable. This method is effectively used to design the SISO FLC.

Decision Feedback Equalizer Algorithms based on Error Entropy Criterion (오차 엔트로피 기준에 근거한 결정 궤환 등화 알고리듬)

  • Kim, Nam-Yong
    • Journal of Internet Computing and Services
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    • v.12 no.4
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    • pp.27-33
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    • 2011
  • For compensation of channel distortion from multipath fading and impulsive noise, a decision feedback equalizer (DFE) algorithm based on minimization of Error entropy (MEE) is proposed. The MEE criterion has not been studied for DFE structures and impulsive noise environments either. By minimizing the error entropy with respect to equalizer weight based on decision feedback structures, the proposed decision feedback algorithm has shown to have superior capability of residual intersymbol interference cancellation in simulation environments with severe multipath and impulsive noise.

A Study on a Basis for the Selection of a Design for Quadratic Model Fits Fearing a Cubic Bias in Multilple Response Case

  • Bae, Wha-Soo
    • Journal of the Korean Statistical Society
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    • v.24 no.1
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    • pp.31-44
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    • 1995
  • In fitting a model, there always exists a discrepancy between the fitted model and the true functional relationship. In measuring this discrepancy, Box and Drapper (1959) used the criterion dividing the discrepancy into two parts which are the bias error part and the variance error one in single response case. In this paper, an optimum design which makes these two types of errors as small as possible is found by extending the Box and Drapper criterion to multiple response situation. Especially, a design is found to meat rotatability conditions when we fit a quadratic model to each response fearing cubic bias. Using the central composite design, an application of general results to a specific case is shown to help understanding the material.

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Balanced Information Potentials for PDF-Distance Algorithms with Constant Modulus Error

  • Kim, Namyong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.4
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    • pp.295-299
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    • 2011
  • Blind equalization techniques have been widely used in wireless communication systems. In this paper, we propose to apply the balanced information potentials to the criterion of minimum Euclidian distance between two PDFs with constant modulus errors for adaptive blind equalizers. One of the two PDFs is constructed with constant modulus error samples and another does with Dirac delta functions. Two information potentials derived from the criterion are balanced in order to have better performance by putting a weighting factor to each information potentials. The proposed blind algorithm has shown in the MSE convergence performance that it can produce enhanced performance by over 3 dB of steady state MSE.

Selection of a Predictive Coverage Growth Function

  • Park, Joong-Yang;Lee, Gye-Min
    • Communications for Statistical Applications and Methods
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    • v.17 no.6
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    • pp.909-916
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    • 2010
  • A trend in software reliability engineering is to take into account the coverage growth behavior during testing. A coverage growth function that represents the coverage growth behavior is an essential factor in software reliability models. When multiple competitive coverage growth functions are available, there is a need for a criterion to select the best coverage growth functions. This paper proposes a selection criterion based on the prediction error. The conditional coverage growth function is introduced for predicting future coverage growth. Then the sum of the squares of the prediction error is defined and used for selecting the best coverage growth function.

Sensitivity Approach of Sequential Sampling Using Adaptive Distance Criterion (적응거리 조건을 이용한 순차적 실험계획의 민감도법)

  • Jung, Jae-Jun;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9 s.240
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    • pp.1217-1224
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    • 2005
  • To improve the accuracy of a metamodel, additional sample points can be selected by using a specified criterion, which is often called sequential sampling approach. Sequential sampling approach requires small computational cost compared to one-stage optimal sampling. It is also capable of monitoring the process of metamodeling by means of identifying an important design region for approximation and further refining the fidelity in the region. However, the existing critertia such as mean squared error, entropy and maximin distance essentially depend on the distance between previous selected sample points. Therefore, although sufficient sample points are selected, these sequential sampling strategies cannot guarantee the accuracy of metamodel in the nearby optimum points. This is because criteria of the existing sequential sampling approaches are inefficient to approximate extremum and inflection points of original model. In this research, new sequential sampling approach using the sensitivity of metamodel is proposed to reflect the response. Various functions that can represent a variety of features of engineering problems are used to validate the sensitivity approach. In addition to both root mean squared error and maximum error, the error of metamodel at optimum points is tested to access the superiority of the proposed approach. That is, optimum solutions to minimization of metamodel obtained from the proposed approach are compared with those of true functions. For comparison, both mean squared error approach and maximin distance approach are also examined.