• Title/Summary/Keyword: Optimal Estimation

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Optimal Measurement Placement for Static Harmonic State Estimation in the Power Systems based on Genetic Algorithm

  • Dehkordl, Behzad Mirzaeian;Fesharaki, Fariborz Haghighatdar;Kiyournarsi, Arash
    • Journal of Electrical Engineering and Technology
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    • v.4 no.2
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    • pp.175-184
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    • 2009
  • In this paper, a method for optimal measurement placement in the problem of static harmonic state estimation in power systems is proposed. At first, for achieving to a suitable method by considering the precision factor of the estimation, a procedure based on Genetic Algorithm (GA) for optimal placement is suggested. Optimal placement by regarding the precision factor has an evident solution, and the proposed method is successful in achieving the mentioned solution. But, the previous applied method, which is called the Sequential Elimination (SE) algorithm, can not achieve to the evident solution of the mentioned problem. Finally, considering both precision and economic factors together in solving the optimal placement problem, a practical method based on GA is proposed. The simulation results are shown an improvement in the precision of the estimation by using the proposed method.

Optimal Power Allocation for Channel Estimation of OFDM Uplinks in Time-Varying Channels

  • Yao, Rugui;Liu, Yinsheng;Li, Geng;Xu, Juan
    • ETRI Journal
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    • v.37 no.1
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    • pp.11-20
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    • 2015
  • This paper deals with optimal power allocation for channel estimation of orthogonal frequency-division multiplexing uplinks in time-varying channels. In the existing literature, the estimation of time-varying channel response in an uplink environment can be accomplished by estimating the corresponding channel parameters. Accordingly, the optimal power allocation studied in the literature has been in terms of minimizing the mean square error of the channel estimation. However, the final goal for channel estimation is to enable the application of coherent detection, which usually means high spectral efficiency. Therefore, it is more meaningful to optimize the power allocation in terms of capacity. In this paper, we investigate capacity with imperfect channel estimation. By exploiting the derived capacity expression, an optimal power allocation strategy is developed. With this developed power allocation strategy, improved performance can be observed, as demonstrated by the numerical results.

Unknown Input Estimation using the Optimal FIR Smoother (최적 유한 임펄스 응답 평활기를 이용한 미지 입력 추정 기법)

  • Kwon, Bo-Kyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.2
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    • pp.170-174
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    • 2014
  • In this paper, an unknown input estimation method via the optimal FIR smoother is proposed for linear discrete-time systems. The unknown inputs are represented by random walk processes and treated as auxiliary states in augmented state space models. In order to estimate augmented states which include unknown inputs, the optimal FIR smoother is applied to the augmented state space model. Since the optimal FIR smoother is unbiased and independent of any a priori information of the augmented state, the estimates of each unknown input are independent of the initial state and of other unknown inputs. Moreover, the proposed method can be applied to stochastic singular systems, since the optimal FIR smoother is derived without the assumption that the system matrix is nonsingular. A numerical example is given to show the performance of the proposed estimation method.

Optimal Search Patterns for Fast Block Matching Motion Estimation (고속 블록정합 움직임 추정을 위한 최적의 탐색 패턴)

  • 임동근;호요성
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.39-42
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    • 2000
  • Motion estimation plays an important role for video coding. In this paper, we derive optimal search patterns for fast block matching motion estimation. By analyzing the block matching algorithm as a function of block shape and size, we can find an optimal search pattern for initial motion estimation. The proposed idea, which has been verified experimentally by computer simulations, can provide an analytical basis for the current MPEG-2 proposals. In order to choose a more compact search pattern for BMA, we exploit the statistical relationship between the motion and the frame difference of each block.

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Design of the optimal inputs for parameter estimation in linear dynamic systems (선형계통의 파라미터 추정을 위한 최적 입력의 설계)

  • 양흥석;이석원;정찬수
    • 제어로봇시스템학회:학술대회논문집
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    • 1986.10a
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    • pp.73-77
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    • 1986
  • Optimal input design problem for linear regression model with constrained output variance has been considered. It is shown that the optimal input signal for the linear regression model can also be realized as an ARMA process. Monte-Carlo simulation results show that the optimal stochastic input leads to comparatively better estimation accuracy than white input signal.

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Performance bounds of optimal FIR filter-under modeling uncertainty (모델 불확실성에 대한 초적 FIR 필터의 성능한계)

  • 유경상;권오규
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.64-69
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    • 1993
  • In this paper we present the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance measure bounds are calculated from the estimation error covariance bounds of the optimal FIR filter and the suboptimal FIR filter. Performance error bounds range are expressed by the upper bounds on the estimation error covariance difference between the real and nominal values in case of the systems with noise uncertainty or model uncertainty. The performance bounds of the systems are derived on the assumption that the system uncertainty and the estimation error covariance are imperfectly known a priori. The estimation error bounds of the optimal FIR filter is compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.

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Estimation error bounds of discrete-time optimal FIR filter under model uncertainty

  • Yoo, Kyung-Sang;Kwon, Oh-Kyu
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.352-355
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    • 1995
  • In this paper, estimation error bounds of the optimal FIR (Finite Impulse Response) filter, which is proposed by Kwon et al.[1, 2], are presented in discrete-time systems with the model uncertainty. Performance bounds are here represented by the upper bounds on the difference of the estimation error covariances between the nominal and real values in case of the systems with the noise or model parameter uncertainty. The estimation error bounds of the discrete-time optimal FIR filter is compared with those of the Kalman filter via a numerical example applied to the simulation problem by Toda and Patel[3]. Simulation results show that the former has robuster performance than the latter.

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A Study on the Estimation Standard of Optimal Construction Duration for Reinforced Concrete Apartment House (철근콘크리트조 공동주택 적정공기 산정기준에 관한 연구)

  • Chun Young-Gee;Lee Gye-Uk;Kim Yang-Taek;Hyun Chang-Tae
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • autumn
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    • pp.531-534
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    • 2001
  • At the beginning of construction, the estimation for the construction duration is very important to effectively control and use labors, builder's equipment, permanent and temporary materials, supplies and utilities, and money. In spite of the importance of the estimation for the construction duration, there is no estimation standard of optimal construction duration in korea. The purpose of this study is to suggest the estimation standard of optimal construction duration that is reasonable and systematical through developing the method for estimating, the construction duration. it is expected to be helpful for estimating, planning and scheduling. The analysis is executed the existing estimation standards and consulting the results of the interviews with the on-site engineers and the concrete compressive stress tests.

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Railroad Travel Demand Estimation System Suggestion (철도수송수요 예측시스템 제안)

  • Min, Jae-Hong
    • Proceedings of the KSR Conference
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    • 2003.10b
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    • pp.3-7
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    • 2003
  • It is very difficult to find optimal train operation plan when analyzing the economic investment using traditional railroad travel demand estimation method. Train operation plan depends on travel demand and vice versa. To solve this problem, this study suggests a demand estimation method to address an optimal train operation scheme with the modal spilt using initial train operation plan and trip assignment.

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Kernel Density Estimation in the L$^{\infty}$ Norm under Dependence

  • Kim, Tae-Yoon
    • Journal of the Korean Statistical Society
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    • v.27 no.2
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    • pp.153-163
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    • 1998
  • We investigate density estimation problem in the L$^{\infty}$ norm and show that the iii optimal minimax rates are achieved for smooth classes of weakly dependent stationary sequences. Our results are then applied to give uniform convergence rates for various problems including the Gibbs sampler.

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