• Title/Summary/Keyword: Least mean squares

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Blind Channel Estimation Under the Time-Invariant Channel Environment (시불변 채널 환경에서의 블라인드 채널 추정)

  • Lee, Gwang-Seok;Kim, Hyun-Deok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.05a
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    • pp.559-562
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    • 2011
  • In this research, We derived Recursive Least Squares(RLS) algorithm with adaptive maximum-likelihood channel estimate for digital pulse amplitude modulated sequence in the presence of intersymbol interference and additive white Gaussian noise. RLS algorithms have better convergence characteristics than conventional algorithms, LMS (Least Mean Squares) algorithms.

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Alternating-Projection-Based Channel Estimation for Multicell Massive MIMO Systems

  • Chen, Yi Liang;Ran, Rong;Oh, Hayoung
    • Journal of information and communication convergence engineering
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    • v.16 no.1
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    • pp.17-22
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    • 2018
  • In massive multiple-input multiple-output (MIMO) systems, linear channel estimation algorithms are widely applied owing to their simple structures. However, they may cause pilot contamination, which affects the subsequent data detection performance. Therefore, herein, for an uplink multicell massive multiuser MIMO system, we consider using an alternating projection (AP) for channel estimation to eliminate the effect of pilot contamination and improve the performance of data detection in terms of the bit error rates as well. Even though the AP is nonlinear, it iteratively searches the best solution in only one dimension, and the computational complexity is thus modest. We have analyzed the mean square error with respect to the signal-to-interference ratios for both the cooperative and non-cooperative multicell scenarios. From the simulation results, we observed that the channel estimation results via the AP benefit the following signal detection more than that via the least squares for both the cooperative and non-cooperative multicell scenarios.

Variance function estimation with LS-SVM for replicated data

  • Shim, Joo-Yong;Park, Hye-Jung;Seok, Kyung-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.5
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    • pp.925-931
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    • 2009
  • In this paper we propose a variance function estimation method for replicated data based on averages of squared residuals obtained from estimated mean function by the least squares support vector machine. Newton-Raphson method is used to obtain associated parameter vector for the variance function estimation. Furthermore, the cross validation functions are introduced to select the hyper-parameters which affect the performance of the proposed estimation method. Experimental results are then presented which illustrate the performance of the proposed procedure.

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KINEMATIC GPS POSITIONING WITH NETWORK-DERIVED IONOSPHERIC DELAYS

  • Hong, Chang-Ki;Grejner-Brzezinska, Dorota A.;Won, Joong-Sun
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.386-389
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    • 2007
  • Currently, fast and accurate long baseline positioning in kinematic mode is a challenging topic, but positional accuracy can be improved with the help of the network-derived external ionospheric corrections. To provide not only ionospheric corrections, but also their variances, satellite-by-satellite interpolation for the ionospheric delays is performed using the least-squares collocation (LSC) method. Satellite-by-satellite interpolation has the advantage in that the vertical projection used in single-layer ionospheric model is not required. Also, more reliable user positioning and the corresponding accuracy assessment can be obtained by providing not only external ionospheric corrections but also their variances. The rover positioning with and without the external ionospheric delays in both rapid-static and kinematic mode was performed and analyzed. The numerical results indicate that the improvement in the positioning quality is achieved using the proposed method. With the TAMDEF network in Antarctica, 18 % improvement in mean time-to-fix in kinematic mode was achieved.

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Large-Sample Comparisons of Statistical Calibration Procedures When the Standard Measurement is Also Subject to Error: The Replicated Case

  • Lee, Seung-Hoon;Yum, Bong-Jin
    • Journal of the Korean Statistical Society
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    • v.17 no.1
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    • pp.9-23
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    • 1988
  • The classicla theory of statistical calibration assumes that the standard measurement is exact. From a realistic point of view, however, this assumption needs to be relaxed so that more meaningful calibration procedures may be developed. This paper presents a model which explicitly considers errors in both standard and nonstandard measurements. Under the assumption that replicated observations are available in the calibration experiment, three estimation techniques (ordinary least squares, grouping least squares, and maximum likelihood estimation) combined with two prediction methods (direct and inverse prediction) are compared in terms of the asymptotic mean square error of prediction.

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Estimation for the Exponential ARMA Model (지수혼합 시계열 모형의 추정)

  • Won Kyung Kim;In Kyu Kim
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.239-248
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    • 1994
  • The Yule-Walker estimator and the approximate conditional least squares estimator of the parameter of the EARMA(1, 1) model are obtained. These two estimators are compared by simulation study. It is shown that the approximate conditional least squares estimator is better in the sense of the mean square error than the Yul-Walker estimator.

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Residual Synchronization Error Elimination in OFDM Baseband Receivers

  • Hu, Xingbo;Huang, Yumei;Hong, Zhiliang
    • ETRI Journal
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    • v.29 no.5
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    • pp.596-606
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    • 2007
  • It is well known that an OFDM receiver is vulnerable to synchronization errors. Despite fine estimations used in the initial acquisition, there are still residual synchronization errors. Though these errors are very small, they severely degrade the bit error rate (BER) performance. In this paper, we propose a residual error elimination scheme for the digital OFDM baseband receiver aiming to improve the overall BER performance. Three improvements on existing schemes are made: a pilot-aided recursive algorithm for joint estimation of the residual carrier frequency and sampling time offsets; a delay-based timing error correction technique, which smoothly adjusts the incoming data stream without resampling disturbance; and a decision-directed channel gain update algorithm based on recursive least-squares criterion, which offers faster convergence and smaller error than the least-mean-squares algorithms. Simulation results show that the proposed scheme works well in the multipath channel, and its performance is close to that of an OFDM system with perfect synchronization parameters.

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Longevity Bond Pricing by a Cohort-based Stochastic Mortality (코호트 사망률을 이용한 장수채권 가격산출)

  • Jho, Jae Hoon;Lee, Kangsoo
    • The Korean Journal of Applied Statistics
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    • v.28 no.4
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    • pp.703-719
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    • 2015
  • We propose an extension of the Lee and Jho (2015) mean reverting the two factor mortality model by incorporating a period-specific cohort effect. We found that the consideration of cohort effect improves the mortality fit of Korea male data above age 65. Parameters are estimated by the weighted least squares method and Metropolis algorithm. We also emphasize that the cohort effect is necessary to choose the base survival index to calculate longevity bond issue price. A key contribution of the article is the proposal and development of a method to calculate the longevity bond price to hedge the longevity risk exposed to Korea National Pension Services.

Short-term Reactive Power Load Forecasting Using Multiple Time-Series Model (다중 시계열 모델을 이용한 단기 부하 무효전력 예측)

  • Lee, Hyo-Sang;Cho, Jong-Man;Park, Woo-Hyun;Kim, Jin-O
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.18 no.5
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    • pp.105-111
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    • 2004
  • This paper shows that active and reactive power load have significant positive relationship and there exist two types of relationship between them using Test Statistics. In investigating the cross plots at every hour, we found out that from 0 to 8 hours, there relationships are linear, while from 9 to 23 hours, they are two piece-wise linear. Also, reactive power loads was estimated and forecasted using active power load as the explanary variable with OLS (Ordinary Least Squares) regression methods. MAPE (Mean Absolute Percentage Error) for each model is calculated for one-hour ahead forecasting.

A Design Method of The Active Noise Controllers for The Perceived Noise Reduction (청감적 소음 감소를 위한 능동소음제어기 설계)

  • Kim, Jong-Ho;Oh, Wong-Eun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.1
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    • pp.179-184
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    • 2019
  • In this paper, we propose a design method of Active Noise Control (ANC) that reduces perceived level of the residual noise. A FELMS (Filtered-E Least Mean Squares) algorithm is used for the ANC system and the NC (noise criteria) is applied as an evaluation criterion of the residual noise. With this structure, we present the allowable spectral shape of the noise shaping filter that minimizes the NC index within the effective operating frequency band of the ANC, and showed that the filter satisfying in the criterion has a lower NC value than the psychoacoustic-based filter used in the previous studies.