• 제목/요약/키워드: Least mean square

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Discrete Multi-Wavelet 변환을 이용한 LMS기반 적응 등화기 설계 (Design of LMS based adaptive equalizer using Discrete Multi-Wavelet Transform)

  • 최윤석;박형근
    • 한국정보통신학회논문지
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    • 제11권3호
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    • pp.600-607
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    • 2007
  • 차세대 이동 멀티미디어 통신에서는 전송지연을 줄이고 버스트 시변채널의 시간변화를 제한하기 위해 버스트 전송이 많이 사용된다. 그러나 채널적응을 위한 훈련 심볼은 짧은 길이의 버스트 데이터에 대해 심각한 문제를 야기할 수 있다. 따라서 심볼에 대한 적응 등화기의 설계에 있어서 짧은 길이의 훈련 심볼과 빠른 수렴을 갖는 적응 알고리즘이 필요로 된다. 본 논문에서는 DMWT (discrete multi-wavelet transform)과 LMS(least mean square) adaptation 을 갖는 적응 등화기를 제안한다. 제안된 등화기는 복잡성의 증가를 최소화하면서도 현재의 transform-domain equalizer보다 빠른 수렴을 갖는다.

기울기 평균 벡터를 사용한 가변 스텝 최소 평균 사승을 사용한 음향 채널 추정기 (An acoustic channel estimation using least mean fourth with an average gradient vector and a self-adjusted step size)

  • 임준석
    • 한국음향학회지
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    • 제37권3호
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    • pp.156-162
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    • 2018
  • LMF(Least Mean Fourth) 알고리즘은 특히 비정규 잡음 상황에서 안정성 및 빠른 수렴성을 나타낼 뿐만아니라 추정 오차도 낮은 것으로 잘 알려져 있다. 최근 LMS (Least Mean Square) 알고리즘 분야에서는 가변 스텝 크기를 적용한 알고리즘들에 대한 관심이 증대되어 왔다. 그 이유는 가변 스텝 크기 LMS가 다양한 환경에서 고정 스텝 크기 LMS보다 우수한 결과를 내기 때문이다. 본 논문에선 LMF에 대한 가변 스텝 크기의 한 방법으로 기울기 평균 벡터를 사용한 가변 스텝 크기를 사용하는 LMF 알고리즘을 제안한다. 제안된 방법은 가변 스텝 크기 LMS와 마찬가지로 고정 스텝 크기 LMF보다 우수할 것이 예상된다. 본 논문은 그 우수성을 시불변 채널과 시변 채널 각각의 채널 환경하에서 시뮬레이션을 통하여 보인다.

퍼지 추론법을 적용한 OFDM 시스템의 LS(Least Square) 채널추정 기법 (Least Square Channel Estimation Scheme of OFDM System using Fuzzy Inference Method)

  • 김남;최정훈
    • 한국콘텐츠학회논문지
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    • 제9권5호
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    • pp.84-90
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    • 2009
  • 본 논문에서는 최근 여러 분야에서 불확실성에 대한 예측을 위해 사용되는 Fuzzy 추론법을 OFDM(Othgonal Frequency Division Multiplexing)의 채널추정 방식에 적용함으로써 향상된 성능과 낮은 복잡도를 갖는 새로운 채널추정 방식을 제안하였다. 제안된 방식은 LS(Least Square) 채널추정 이전에 Pilot을 이용하여 Fuzzy추론법에 의하여 채널의 통계적 특성을 계산하고 이에 대한 보간을 해 줌으로써 채널추정 성능을 향상시키는 방식이다. QPSK(Quadrature Phase Shift Keying)를 적용한 시뮬레이션 결과 제안된 채널추정 방식은 MSE(Mean Square Error)가 $10^{-3}$인 지점에서 MMSE(Mimimum Mean Square Error) 채널추정 방식보다는 약 1.3 dB 정도 성능이 열화되는 것으로 나타났지만 LS 채널 추정 방식과 비교하면 약 5.5 dB 정도의 성능 이득이 있는 것으로 분석되었으며, SER(Symbol Error Rate)은 SNR(Signal to Noise Ratio)이 20 dB인 지점에서 MMSE 채널추정 방식과 제안된 채널추정방식이 각각 $10^{-1.96}$, $10^{-1.93}$ 정도로 유사한 성능을 보이는 것으로 분석되었고, LS 채널추정 방식 보다 약 $10^{-0.35}$ 정도 제안된 방식의 성능이 향상된 것으로 분석되었다.

An Implementation of Discrete Mathematical Model for ECG waveform

  • Yimman, Surapun;Deeudom, Mongkon;Ittisariyanon, Jirawat;Junnapiya, Somyot;Dejhan, Kobchai
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.852-856
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    • 2005
  • This paper proposes a new design of the ECG simulator with high resolution by using small amount of memories based on discrete least square estimation equations instead of reading the stored data inside the look-up table. The experimental results have shown that the ECG simulator using discrete least square estimation equations can display the bipolar limb leads ECG signals with low PRD (percent root-mean-square difference) while taking the less amount of memories than the previous method which used the look-up table to store ECG data for ECG simulation.

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주파수 선택성 페이딩 채널에서 보상 알고리즘의 수렴특성 (Convergence Characteristics of Compensation Algorithm in Frequency Selective Fading Channel)

  • 이승대
    • 한국컴퓨터산업학회논문지
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    • 제8권4호
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    • pp.263-268
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    • 2007
  • 본 논문에서는 시불변 전송 채널 및 주파수 선택성 페이딩 채널에서 최소 제곱 평균 알고리즘과 순차적 최소 제곱 알고리즘에 선형 탭 지연선 구조를 도입하여 보상 알고리즘의 제곱 평균 에러 특성을 고찰하였다. 또한 기존의 방식에서 사용하는 단일 탭 갱신 알고리즘과 본 논문에서 제안한 다중 탭 갱신 알고리즘을 비교, 분석하고 이를 수렴 특성 관점에서 고찰하였다.

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Estimation of Ridge Regression Under the Integrate Mean Square Error Cirterion

  • Yong B. Lim;Park, Chi H.;Park, Sung H.
    • Journal of the Korean Statistical Society
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    • 제9권1호
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    • pp.61-77
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    • 1980
  • In response surface experiments, a polynomial model is often used to fit the response surface by the method of least squares. However, if the vectors of predictor variables are multicollinear, least squares estimates of the regression parameters have a high probability of being unsatisfactory. Hoerland Kennard have demonstrated that these undesirable effects of multicollinearity can be reduced by using "ridge" estimates in place of the least squares estimates. Ridge regrssion theory in literature has been mainly concerned with selection of k for the first order polynomial regression model and the precision of $\hat{\beta}(k)$, the ridge estimator of regression parameters. The problem considered in this paper is that of selecting k of ridge regression for a given polynomial regression model with an arbitrary order. A criterion is proposed for selection of k in the context of integrated mean square error of fitted responses, and illustrated with an example. Also, a type of admissibility condition is established and proved for the propose criterion.criterion.

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재순환 버퍼 RLS 알고리즘에서 가중치 갱신을 이용한 개선된 수렴 특성에 관한 연구 (A study on the Improved Convergence Characteristic over Weight Updating of Recycling Buffer RLS Algorithm)

  • 나상동
    • 한국통신학회논문지
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    • 제25권5B호
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    • pp.830-841
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    • 2000
  • We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at iteration a upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RL algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the (B+1)times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

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Influence of stress level on uniaxial ratcheting effect and ratcheting strain rate in austenitic stainless steel Z2CND18.12N

  • Chen, Xiaohui;Chen, Xu;Chen, Haofeng
    • Steel and Composite Structures
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    • 제27권1호
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    • pp.89-94
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    • 2018
  • Uniaxial ratcheting behavior of Z2CND18.12N austenitic stainless steel used nuclear power plant piping material was studied. The results indicated that ratcheting strain increased with increasing of stress amplitude under the same mean stress and different stress amplitude, ratcheting strain increased with increasing of mean stress under the same stress amplitude and different mean stress. Based on least square method, a suitable method to arrest ratcheting by loading the materials was proposed, namely determined method of zero ratcheting strain rate. Zero ratcheting strain rate occur under specified mean stress and stress amplitudes. Moreover, three dimensional ratcheting boundary surface graph was established with stress amplitude, mean stress and ratcheting strain rate. This represents a graphical surface zone to study the ratcheting strain rates for various mean stress and stress amplitude combinations. The graph showed the ratcheting behavior under various combinations of mean and amplitude stresses. The graph was also expressed with the help of experimental results of certain sets of mean and stress amplitude conditions. Further, experimentation cost and time can be saved.

Resistant GPA algorithms based on the M and LMS estimation

  • Hyun, Geehong;Lee, Bo-Hui;Choi, Yong-Seok
    • Communications for Statistical Applications and Methods
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    • 제25권6호
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    • pp.673-685
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    • 2018
  • Procrustes analysis is a useful technique useful to measure, compare shape differences and estimate a mean shape for objects; however it is based on a least squares criterion and is affected by some outliers. Therefore, we propose two generalized Procrustes analysis methods based on M-estimation and least median of squares estimation that are resistant to object outliers. In addition, two algorithms are given for practical implementation. A simulation study and some examples are used to examine and compared the performances of the algorithms with the least square method. Moreover since these resistant GPA methods are available for higher dimensions, we need some methods to visualize the objects and mean shape effectively. Also since we have concentrated on resistant fitting methods without considering shape distributions, we wish to shape analysis not be sensitive to particular model.

파티클 필터기법을 통한 비선형 피로모델 개발 연구 (Development of Nonlinear Fatigue Model Based on Particle Filter Method)

  • 문성호
    • 한국도로학회논문집
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    • 제18권4호
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    • pp.63-68
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    • 2016
  • PURPOSES : The nonlinear model of fatigue cracking is typically used for determining the maintenance period. However, this requires that the model parameters be known. In this study, the particle filter (PF) method was used to determine various statistical parameters such as the mean and standard deviation values for the nonlinear model of fatigue cracking. METHODS : The PF method was used to determine various statistical parameters for the nonlinear model of fatigue cracking, such as the mean and standard deviation. RESULTS : On comparing the values obtained using the PF method and the least square (LS) method, it was found that PF method was suitable for determining the statistical parameters to be used in the nonlinear model of fatigue cracking. CONCLUSIONS : The values obtained using the PF method were as accurate as those obtained using the LS method. Furthermore, reliability design can be applied because the statistical parameters of mean and standard deviation can be obtained through the PF method.