Chee-Hyun Park

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In wireless communications, knowledge of the signal-to-noise ratio is required in diverse communication applications. In this paper, we derive the variance of the maximum likelihood estimator in the data-aided and non-data-aided schemes for determining the optimal shrinkage factor. The shrinkage factor is usually the constant that is multiplied by the(More)
a r t i c l e i n f o a b s t r a c t Shrinkage factor Minimum mean squared error Minimum bias Weighted least squares Time-of-arrival In this paper, we propose two novel source localization methods; one is the shrinkage estimator with the minimum mean squared error criterion, and the other is the shrinkage estimator with the minimum bias criterion. The mean(More)
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract— This paper presents two closed-form localization algorithms, a general algorithm and a co-located algorithm, for distributed multiple-input multiple-output (MIMO) radar systems. In(More)
BACKGROUND Current oscillometric blood pressure measurement devices generally provide only single-point estimates for systolic and diastolic blood pressures and rarely provide confidence ranges for these estimates. A novel methodology to obtain confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates from a(More)
Breakdown point Hodges–Lehmann estimator Influence function Robust statistics a b s t r a c t In this paper, we propose an NLOS source localization method that utilizes the robust statistics, namely, the α-trimmed mean and Hodges–Lehmann estimator. The root mean squared error average of the proposed methods is similar to that of the other estimators such as(More)
Although the systolic and diastolic blood pressure ratios (SBPRs and DBPRs) based on the conventional maximum amplitude algorithm (MAA) are assumed to be fixed; this assumption is not valid. In this paper, we present an improved Gaussian mixture regression (IGMR) approach that can accurately measure blood pressure. The SBPR and DBPR are estimated by using(More)
We propose a line-of-sight (LOS)/non-line-of-sight (NLOS) mixture source localization algorithms that utilize the weighted block Newton (WBN) and variable step size WBN (VSSWBN) method, in which the weighting matrix is determined in the form of the inverse of the squared error or as an exponential function with a negative exponent. The proposed WBN and(More)