• Title/Summary/Keyword: Density estimator

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BLUE-Based Channel Estimation Technique for Amplify and Forward Wireless Relay Networks

  • PremKumar, M.;SenthilKumaran, V.N.;Thiruvengadam, S.J.
    • ETRI Journal
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    • v.34 no.4
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    • pp.511-517
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    • 2012
  • The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.

Vision-Based Indoor Object Tracking Using Mean-Shift Algorithm (평균 이동 알고리즘을 이용한 영상기반 실내 물체 추적)

  • Kim Jong-Hun;Cho Kyeum-Rae;Lee Dae-Woo
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.8
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    • pp.746-751
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    • 2006
  • In this paper, we present tracking algorithm for the indoor moving object. We research passive method using a camera and image processing. It had been researched to use dynamic based estimators, such as Kalman Filter, Extended Kalman Filter and Particle Filter for tracking moving object. These algorithm have a good performance on real-time tracking, but they have a limit. If the shape of object is changed or object is located on complex background, they will fail to track them. This problem will need the complicated image processing algorithm. Finally, a large algorithm is made from integration of dynamic based estimator and image processing algorithm. For eliminating this inefficiency problem, image based estimator, Mean-shift Algorithm is suggested. This algorithm is implemented by color histogram. In other words, it decide coordinate of object's center from using probability density of histogram in image. Although shape is changed, this is not disturbed by complex background and can track object. This paper shows the results in real camera system, and decides 3D coordinate using the data from mean-shift algorithm and relationship of real frame and camera frame.

Robust Total Least Squares Method and its Applications to System Identifications (견인한 완전최소자승법과 시스템 식별에의 적용)

  • Kim, Jin-Young;Choi, Seung-Ho
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.4
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    • pp.93-97
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    • 1996
  • The Total Least Squares(TLS) method is an unbiased estimator for solving overdetermined sets of linear equations Ax${\simeq}$b when errors occur in all data. However, as well as Least Squares(LS) method it doesn't show robustness while the errors have a heavy tailed probability density function. In this paper we proposed a robust method of TLS (Robust TLS, ROTLS) based on the characteristics of TLS solution. And the ROTLS is verified by applying it to system identification problems.

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Cosmology with peculiar velocity surveys

  • Qin, Fei
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.2
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    • pp.43.5-44
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    • 2021
  • In the local Universe, the gravitational effects of mass density fluctuations exert perturbations on galaxies' redshifts on top of Hubble's Law, called 'peculiar velocities'. These peculiar velocities provide an excellent way to test the cosmological model in the nearby Universe. In this talk, we present new cosmological constraints using peculiar velocities measured with the 2MASS Tully-Fisher survey (2MTF), 6dFGS peculiar-velocity survey (6dFGSv), the Cosmicflows-3 and Cosmicflows-4TF compilation. Firstly, the dipole and the quadrupole of the peculiar velocity field, commonly named 'bulk flow' and 'shear' respectively, enable us to test whether our cosmological model accurately describes the motion of galaxies in the nearby Universe. We develop and use a new estimators that accurately preserves the error distribution of the measurements to measure these moments. In all cases, our results are consistent with the predictions of the Λ cold dark matter model. Additionally, measurements of the growth rate of structure, fσ8 in the low-redshift Universe allow us to test different gravitational models. We developed a new estimator of the "momentum" (density weighted peculiar velocity) power spectrum and use joint measurements of the galaxy density and momentum power spectra to place new constraints on the growth rate of structure from the combined 2MTF and 6dFGSv data. We recover a constraint of fσ8=0.404+0.082-0.081 at an effective redshift zeff=0.03. This measurement is also fully consistent with the expectations of General Relativity and the Λ Cold Dark Matter cosmological model.

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Tiny Pores observed by HINODE/SOT

  • Cho, Kyung-Suk;Bong, Su-Chan;Chae, Jong-Chul;Kim, Yeon-Han;Park, Young-Deuk
    • The Bulletin of The Korean Astronomical Society
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    • v.35 no.2
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    • pp.49.1-49.1
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    • 2010
  • The study of pores, small penumbraless sunspots, can give us a chance to understand how strong magnetic fields interact with convective motions in the photosphere. For a better understanding of this interaction, we investigate the temporal variation of several tiny pores smaller than 2". These pores were observed by the Solar Optical Telescope (SOT) onboard Hinode on 2006 December 29. We have analyzed the high resolution spectropolarimetric (SP) data and the G-band filtergrams taken during the observation. Magnetic flux density and Doppler velocities of the pores are estimated by applying the center of gravity (COG) method to the SP data. The horizontal motions in and around the pores are tracked by adopting the Nonlinear Affine Velocity Estimator (NAVE) method to the G-band filter images. As results, we found the followings. (1) Darkness of pores is positively correlated with magnetic flux density. (2) Downflows always exist inside and around the pores. (3) The speed of downflows inside the pores is negatively correlated with their darkness. (4) The pores are surrounded by strong downflows. (5) Brightness changes of the pores are correlated with the divergence of mass flow (correlation coefficient > 0.9). (6) The pores in the growing phase are associated with the converging flow pattern and the pores in the decay phase with the diverging flow pattern. Our results support the idea that a pore grows as magnetic flux density increases due to the convergence of ambient mass flow and it decays with the decrease of the flux density due to the diverging mass flow.

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Likelihood Approximation of Diffusion Models through Approximating Brownian Bridge (브라운다리 근사를 통한 확산모형의 우도 근사법)

  • Lee, Eun-kyung;Sim, Songyong;Lee, Yoon Dong
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.895-906
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    • 2015
  • Diffusion is a mathematical tool to explain the fluctuation of financial assets and the movement of particles in a micro time scale. There are ongoing statistical trials to develop an estimation method for diffusion models based on likelihood. When we estimate diffusion models by applying the maximum likelihood estimation method on data observed at discrete time points, we need to know the transition density of the diffusion. In order to approximate the transition densities of diffusion models, we suggests the method to approximate the path integral of the random process with normal random variables, and compare the numerical properties of the method with other approximation methods.

Asymptotic Properties of Variance Change-point in the Long-memory Process

  • Chu Minjeong;Cho Sinsup
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.23-26
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    • 2000
  • It is noted that many econometric time series have long-memory properties. A long-memory process, or strongly dependent process, is characterized by hyperbolic decaying autocorrelations and unbounded spectral density at the origin. Since the long-memory property can be observed by data obtained from rather a long period, there is some possibility of parameter change in the process. In this paper, we consider the estimation of change-point when there is a change in the variance of a long-memory process. The estimator is based on some reasonable statistic and the consistency is shown using Taqqu's strong reduction theorem

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Servo Design for High-TPI Hard Disk Drives Using a Delay-Accommodating State Estimator

  • Kim, Young-Hoon;Chu, Sang-Hoon;Kang, S.W.;Oh, D.H.;Han, Y.S.;Hwang, T.Y.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.11b
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    • pp.134-139
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    • 2002
  • This paper presents a servo design method for high track-density hard disk drives, in which the plant time delay, mainly due to the processor computation time, is taken into account. The key idea behind the proposed design method is to incorporate the delay model into the output equation of the state-space representation for the plant model; thereby, the delay is accounted for by a standard state observer in a natural manner, with simplified state equations as compared to those for conventional methods. The results from practical application confirm that the proposed method is quite effective in realizing a high-bandwidth servo system in hard disk drives.

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Anomaly Detection in Medical Wireless Sensor Networks

  • Salem, Osman;Liu, Yaning;Mehaoua, Ahmed
    • Journal of Computing Science and Engineering
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    • v.7 no.4
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    • pp.272-284
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    • 2013
  • In this paper, we propose a new framework for anomaly detection in medical wireless sensor networks, which are used for remote monitoring of patient vital signs. The proposed framework performs sequential data analysis on a mini gateway used as a base station to detect abnormal changes and to cope with unreliable measurements in collected data without prior knowledge of anomalous events or normal data patterns. The proposed approach is based on the Mahalanobis distance for spatial analysis, and a kernel density estimator for the identification of abnormal temporal patterns. Our main objective is to distinguish between faulty measurements and clinical emergencies in order to reduce false alarms triggered by faulty measurements or ill-behaved sensors. Our experimental results on both real and synthetic medical datasets show that the proposed approach can achieve good detection accuracy with a low false alarm rate (less than 5.5%).

Reduction of Torque Ripple of Permanent Magnet Synchronous Motor (영구자석 동기전동기의 토크 리플 저감 운전)

  • Lee, D.H.;Lee, J.H.;Kim, Y.S.;Kim, J.H.;Kwon, Y.A.
    • Proceedings of the KIEE Conference
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    • 2001.07b
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    • pp.918-920
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    • 2001
  • PMSM drives are widely used in industrial and residential applications because of high efficiency, high power density and high performance. For better performance of PMSM, however, torque ripples should be reduced. This paper investigates a reduction of torque ripple due to the unsinusoidal flux linkage produced by the shapes of stator slot and magnetic pole. To minimize torque ripple, a simple flux estimator is proposed. This method iteratively compensates the distributed flux linkage from an error between the measured and estimated currents. The proposed algorithm is verified through simulation.

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