• Title, Summary, Keyword: estimation

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A Comparative Study of Small Area Estimation Methods (소지역 추정법에 관한 비교연구)

  • Park, Jong-Tae;Lee, Sang-Eun
    • Journal of the Korean Data and Information Science Society
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    • v.12 no.2
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    • pp.47-55
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    • 2001
  • Usually estimating the means is used for statistical inference. However depending the purpose of survey, sometimes totals will give the better and more meaningful in statistical inference than the means. Here in this study, we dealt with the unemployment population of small areas with using 4 different small area estimation methods: Direct, Synthetic, Composite, Bayes estimation. For all the estimates considered in this study, the average of absolute bias and men square error were obtained in the Monte Carlo Study which was simulated using data from 1998 Economic Active Population Survey in Korea.

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Performance Analysis of Location Estimation Algorithm Using an Enhanced Decision Scheme for RTLS

  • Lee Hyun-Jae;Jeong Seung-Hee;Oh Chang-Heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.397-401
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    • 2006
  • In this paper, we proposed a high precision location estimation algorithm using an enhanced decision scheme for RTLS and analyzed its performance in point of an average estimation error distance at 2D coordinates searching area, $300m\times300m$ and LOS propagation environments. Also the performance was compared with that of conventional TDOA algorithm according to the number of available reader and received sub-blink. From the results, we confirmed that the proposed location estimation algorithm using an enhanced decision scheme was able to improve an estimation accuracy even in boundary region of searching area. Moreover, effectively reduced an error distance in entire searching area so that increased the stability of location estimation in RTLS. Therefore, we verified that the proposed algorithm provided a more higher estimation accuracy and stability than conventional TDOA.

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An Efficient Global Motion Estimation based on Robust Estimator

  • Joo, Jae-Hwan;Choe, Yoon-Sik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.408-412
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    • 2009
  • In this paper, a new efficient algorithm for global motion estimation is proposed. This algorithm uses a previous 4-parameter model based global motion estimation algorithm and M-estimator for improving the accuracy and robustness of the estimate. The first algorithm uses the block based motion vector fields and which generates a coarse global motion parameters. And second algorithm is M-estimator technique for getting precise global motion parameters. This technique does not increase the computational complexity significantly, while providing good results in terms of estimation accuracy. In this work, an initial estimation for the global motion parameters is obtained using simple 4-parameter global motion estimation approach. The parameters are then refined using M-estimator technique. This combined algorithm shows significant reduction in mean compensation error and shows performance improvement over simple 4-parameter global motion estimation approach.

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Selection of Machining Parameters of Electric Discharge Wire Cut Using 2-Step Neuro-estimation (2단계 신경망 추정에 의한 와이어 컷 방전 가공 조건 선정)

  • Lee, Keon-Beom;Ju, Sang-Yoon;Wang, Gi-Nam
    • IE interfaces
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    • v.10 no.3
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    • pp.125-132
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    • 1997
  • We proposed a 2-step neural network approach for estimating machining parameters of electric discharge wire cut. The first step net, which is described as a backward neuro-estimation, is designed for estimating coarse cutting parameters while the second phase net, as a polishing forward neuro-estimation, is utilized for determining fine parameters. Sequential estimation procedure, based on backward and forward net, is performed using the net's approximation capability which is M to 1 and 1 to M mapping property. Experimental results an given to evaluate the accuracy of the proposed 2-step neuro-estimation.

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On-line System Identification using State Observer

  • Park, Duck-Gee;Hong, Suk-Kyo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.2538-2541
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    • 2005
  • This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

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Joint Estimation of TOA and DOA in IR-UWB System Using Sparse Representation Framework

  • Wang, Fangqiu;Zhang, Xiaofei
    • ETRI Journal
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    • v.36 no.3
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    • pp.460-468
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    • 2014
  • This paper addresses the problem of joint time of arrival (TOA) and direction of arrival (DOA) estimation in impulse radio ultra-wideband systems with a two-antenna receiver and links the joint estimation of TOA and DOA to the sparse representation framework. Exploiting this link, an orthogonal matching pursuit algorithm is used for TOA estimation in the two antennas, and then the DOA parameters are estimated via the difference in the TOAs between the two antennas. The proposed algorithm can work well with a single measurement vector and can pair TOA and DOA parameters. Furthermore, it has better parameter-estimation performance than traditional propagator methods, such as, estimation of signal parameters via rotational invariance techniques algorithms matrix pencil algorithms, and other new joint-estimation schemes, with one single snapshot. The simulation results verify the usefulness of the proposed algorithm.

Noise Estimation Using Edge Detection (에지 검출을 이용한 잡음 예측)

  • Kim, Young-Ro;Dong, Sung-Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.281-286
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    • 2013
  • In this paper, we propose a noise estimation method using edge detection. It is a filter-based noise estimation method. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use a modified rational filter which is robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of images and has better results than those of conventional filter-based noise estimation methods.

Angle-Range-Polarization Estimation for Polarization Sensitive Bistatic FDA-MIMO Radar via PARAFAC Algorithm

  • Wang, Qingzhu;Yu, Dan;Zhu, Yihai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2879-2890
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    • 2020
  • In this paper, we study the estimation of angle, range and polarization parameters of a bistatic polarization sensitive frequency diverse array multiple-input multiple-output (PSFDA-MIMO) radar system. The application of polarization sensitive array in receiver is explored. A signal model of bistatic PSFDA-MIMO radar system is established. In order to utilize the multi-dimensional structure of array signals, the matched filtering radar data can be represented by a third-order tensor model. A joint estimation of the direction-of-departure (DOD), direction-of-arrival (DOA), range and polarization parameters based on parallel factor (PARAFAC) algorithm is proposed. The proposed algorithm does not need to search spectral peaks and singular value decomposition, and can obtain automatic pairing estimation. The method was compared with the existing methods, and the results show that the performance of the method is better. Therefore, the accuracy of the parameter estimation is further improved.

An Alternative State Estimation Filtering Algorithm for Temporarily Uncertain Continuous Time System

  • Kim, Pyung Soo
    • Journal of Information Processing Systems
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    • v.16 no.3
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    • pp.588-598
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    • 2020
  • An alternative state estimation filtering algorithm is designed for continuous time systems with noises as well as control input. Two kinds of estimation filters, which have different measurement memory structures, are operated selectively in order to use both filters effectively as needed. Firstly, the estimation filter with infinite memory structure is operated for a certain continuous time system. Secondly, the estimation filter with finite memory structure is operated for temporarily uncertain continuous time system. That is, depending on the presence of uncertainty, one of infinite memory structure and finite memory structure filtered estimates is operated selectively to obtain the valid estimate. A couple of test variables and declaration rule are developed to detect uncertainty presence or uncertainty absence, to operate the suitable one from two kinds of filtered estimates, and to obtain ultimately the valid filtered estimate. Through computer simulations for a continuous time aircraft engine system with different measurement memory lengths and temporary model uncertainties, the proposed state estimation filtering algorithm can work well in temporarily uncertain as well as certain continuous time systems. Moreover, the proposed state estimation filtering algorithm shows remarkable superiority to the infinite memory structure filtering when temporary uncertainties occur in succession.

A study on analyzing the improvement of the students' estimation capabilities of length measurement in measurement instruction with various uses of estimation strategy (초등학생들의 다양한 어림 전략을 통한 길이 어림 분석)

  • Lee, SooJin;Kim, Min Kyeong
    • Education of Primary School Mathematics
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    • v.20 no.1
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    • pp.1-18
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    • 2017
  • The purpose of this study is the reorganization of the curriculum on the measurement, a part of the second grade math curriculum, for the improvement of the estimation capability in the elementary school students. Research questions were as follows: (1) how are the estimation capabilities of the students who have taken lessons on the diversified estimation strategies? and (2) how are the mathematical writing capabilities of the students who have taken lessons on the diversified estimation strategies? The study using reconstructed lessons was conducted on 18 second grade students in an elementary school located in Seoul. Results show that the students' estimation capabilities and have improved. They started to use 'about' when writing estimation results, different from writing the accurate measurements. Measurement errors were gradually reduced, ending up with a student who could accurately estimate exactly 1m. In addition, their estimation capabilities in using appropriate estimation strategy and writing skills describing the estimation strategy have improved.