• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.54-76
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• 1988

In Part Ⅰ of the paper, we have developed various block least mean-square (BLMS) adaptive digital filters (ADF's) based on a unified matrix treatment. In Part Ⅱ we analyze the convergence behaviors of the self-orthogonalizing frequency-domain BLMS (FBLMS) ADF and the unconstrained FBLMS (UFBLMS) ADF both for the overlap-save and overlap-add sectioning methods. We first show that, unlike the FBLMS ADF with a constant convergence factor, the convergence behavior of the self-orthogonalizing FBLMS ADF is governed by the same autocorrelation matrix as that of the UFBLMS ADF. We then show that the optimum solution of the UFBLMS ADF is the same as that of the constrained FBLMS ADF when the filter length is sufficiently long. The mean of the weight vector of the UFBLMS ADF is also shown to converge to the optimum Wiener weight vector under a proper condition. However, the steady-state mean-squared error(MSE) of the UFBLMS ADF turns out to be slightly worse than that of the constrained algorithm if the same convergence constant is used in both cases. On the other hand, when the filter length is not sufficiently long, while the constrained FBLMS ADF yields poor performance, the performance of the UFBLMS ADF can be improved to some extent by utilizing its extended filter-length capability. As for the self-orthogonalizing FBLMS ADF, we study how we can approximate the autocorrelation matrix by a diagonal matrix in the frequency domain. We also analyze the steady-state MSE's of the self-orthogonalizing FBLMS ADF's with and without the constant. Finally, we present various simulation results to verify our analytical results.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.21-30
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• 2022

Objectives: The purpose of this study is to suggest an optimal method by comparing the analysis methods of work environment measurement datasets including left-censored data where one or more measurements are below the limit of detection (LOD). Methods: A computer program was used to generate left-censored datasets for various combinations of censoring rate (1% to 90%) and sample size (30 to 300). For the analysis of the censored data, the simple substitution method (LOD/2), β-substitution method, maximum likelihood estimation (MLE) method, Bayesian method, and regression on order statistics (ROS)were all compared. Each method was used to estimate four parameters of the log-normal distribution: (1) geometric mean (GM), (2) geometric standard deviation (GSD), (3) 95th percentile (X95), and (4) arithmetic mean (AM) for the censored dataset. The performance of each method was evaluated using relative bias and relative root mean squared error (rMSE). Results: In the case of the largest sample size (n=300), when the censoring rate was less than 40%, the relative bias and rMSE were small for all five methods. When the censoring rate was large (70%, 90%), the simple substitution method was inappropriate because the relative bias was the largest, regardless of the sample size. When the sample size was small and the censoring rate was large, the Bayesian method, the β-substitution method, and the MLE method showed the smallest relative bias. Conclusions: The accuracy and precision of all methods tended to increase as the sample size was larger and the censoring rate was smaller. The simple substitution method was inappropriate when the censoring rate was high, and the β-substitution method, MLE method, and Bayesian method can be widely applied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.967-983
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• 2003

In wireless spread-spectrum communication systems utilizing PN (pseudo noise) sequences, a variety of noise sources from the channel affect the data reception performance. Among them, in this paper we are concerned with the narrowband interference that may arise from the use of the spectral bands overlapped by the existing narrowband users or the intentional jammers as in military communication. The effect of this interference can be reduced to some extent at the receiver with the PN demodulation by processing gain. It is known, however, that when the interferers are strong, the reduction cannot be sufficient and thereby requiring the extra use of narrowband interference cancellers (NIC's) at the receivers. A class of adaptive NIC's are studied here based on different two cost functions. One is the chip mean-squared error (MSE) computed prior to the PN demodulation and used in the conventional cancellers. Since thses conventional cancellers should be operated at the chip rate, the computational requirements are enormous. The other is the symbol MSE computed after the PN demodulation in which case the weights of the NIC's can be updated at a lot lower symbol rate. To compare the performance of these NIC's, we derive a common measure of performance, i.e., the symbol MSE after the PN demodulation. The analytical results are verified by computer simulation. As a result, it is shown that the cancellation capability of the symbol-rate NIC's are similar or better than the conventional one while the computational complexity can be reduced a lot.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.9
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• pp.1349-1354
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• 2019

Objective: The objective of this study was to determine the best approach for handling missing records of first to successful insemination (FS) in Japanese Black heifers. Methods: Of a total of 2,367 records of heifers born between 2003 and 2015 used, 206 (8.7%) of open heifers were missing. Four penalty methods based on the number of inseminations were set as follows: C1, FS average according to the number of inseminations; C2, constant number of days, 359; C3, maximum number of FS days to each insemination; and C4, average of FS at the last insemination and FS of C2. C5 was generated by adding a constant number (21 d) to the highest number of FS days in each contemporary group. The bootstrap method was used to compare among the 5 methods in terms of bias, mean squared error (MSE) and coefficient of correlation between estimated breeding value (EBV) of non-censored data and censored data. Three percentages (5%, 10%, and 15%) were investigated using the random censoring scheme. The univariate animal model was used to conduct genetic analysis. Results: Heritability of FS in non-censored data was $0.012{\pm}0.016$, slightly lower than the average estimate from the five penalty methods. C1, C2, and C3 showed lower standard errors of estimated heritability but demonstrated inconsistent results for different percentages of missing records. C4 showed moderate standard errors but more stable ones for all percentages of the missing records, whereas C5 showed the highest standard errors compared with noncensored data. The MSE in C4 heritability was $0.633{\times}10^{-4}$, $0.879{\times}10^{-4}$, $0.876{\times}10^{-4}$ and $0.866{\times}10^{-4}$ for 5%, 8.7%, 10%, and 15%, respectively, of the missing records. Thus, C4 showed the lowest and the most stable MSE of heritability; the coefficient of correlation for EBV was 0.88; 0.93 and 0.90 for heifer, sire and dam, respectively. Conclusion: C4 demonstrated the highest positive correlation with the non-censored data set and was consistent within different percentages of the missing records. We concluded that C4 was the best penalty method for missing records due to the stable value of estimated parameters and the highest coefficient of correlation.

• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.203-215
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• 2023

Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R² and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R² value was 0.27 and in set II, LightGBM was the best model with the highest R² value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R² value of 0.56 and the lowest MSE of 174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperative lung function.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.335-343
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• 2006

We have designed the system that measure one channel ECG by two electrode and extract real-time EDR with more related resipiration and comportable to subject by using conductive textile. On the assumption that relation between RL electrode and potential measurement electrode is coupled with RC connected model, we designed RL drive output to feedback two electrode for reduction of common mode signal. The conductive textile which was used for two ECG electrode was offered more comfort during night sleep in bed than any other method using attachments. In the method of single-lead EDR, R wave point or QRS interval area could be used for EDR estimation in traditional method, it is, so to speak, the amplitude modulation(AM) method for EDR. Alternatively, R-R interval could be used for frequency modulation(FM) method based on Respiratory Sinus Arrhythmia(RSA). For evaluation of performance on AM EDR and FM EDR from 14 subject, ECG lead III was measured. Each EDR was compared with both temperature around nose(direct measurement of respiration) and respiration signal from thoracic belt(indirect measurement of respiration) on mean squared error(MSE), cross correlation(Xcorr), and Coherence. The upsampling interpolation technique of multirate signal processing is applied to interpolating data instead of cubic spline interpolation. As a result, we showed the real-time EDR extraction processing to be implemented at micro-controller.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.53 no.5
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• pp.699-706
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• 2020

Predictive models in food microbiology are used for predicting microbial growth or death rates using mathematical and statistical tools considering the intrinsic and extrinsic factors of food. This study developed predictive growth models for Bacillus cereus on dried laver Pyropia pseudolinearis stored at different temperatures (5, 10, 15, 20, and 25℃). Primary models developed for specific growth rate (SGR), lag time (LT), and maximum population density (MPD) indicated a good fit (R²≥0.98) with the Gompertz equation. The SGR values were 0.03, 0.08, and 0.12, and the LT values were 12.64, 4.01, and 2.17 h, at the storage temperatures of 15, 20, and 25℃, respectively. Secondary models for the same parameters were determined via nonlinear regression as follows: SGR=0.0228-0.0069*T₁+0.0005*T₁²; LT=113.0685-9.6256*T₁+0.2079*T₁²; MPD=1.6630+0.4284*T₁-0.0080*T₁² (where T₁ is the storage temperature). The appropriateness of the secondary models was validated using statistical indices, such as mean squared error (MSE<0.01), bias factor (0.99≤B_f≤1.07), and accuracy factor (1.01≤A_f≤1.14). External validation was performed at three random temperatures, and the results were consistent with each other. Thus, these models may be useful for predicting the growth of B. cereus on dried laver.

• Atmosphere
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• v.16 no.2
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• pp.125-139
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• 2006

Precipitation forecasts from MM5 have been verified for the period 1989-2001 over Yeongdong region to show a tendency of model forecast. We select 57 events which are related with the heavy snowfall in Yeongdong region. They are classified into three precipitation types; mountain type, cold-coastal type, and warm type. The threat score (TS), the probability of detection (POD), and the false-alarm rate (FAR) are computed for categorical verification and the mean squared error (MSE) is also computed for scalar accuracy measures. In the case of POD, warm, mountain, and cold-coastal precipitation type are 0.71, 0.69, and 0.55 in turn, respectively. In aspect of quantitative verification, mountain and cold-coastal type are relatively well matched between forecasts and observations, while for warm type MM5 tends to overestimate precipitation. There are 12 events for the POD below 0.2, mountain, cold-coastal, warm type are 2, 7, 3 events, respectively. Most of their precipitation are distributed over the East Sea nearby Yeongdong region. These events are also shown when there are no or very weak easterlies in the lower troposphere. Even in the case that we use high resolution sea surface temperature (about 18 km) for the boundary condition, there are not much changes in the wind direction to compare that with low resolution sea surface temperature (about 100 km).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.205-213
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• 2011

The Long Term Evolution (LTE) system is designed to provide a high quality data service for fast moving mobile users. It is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the training samples which are systematically built within the transmitting data. Either a preamble or a lattice type is used for the distribution of training samples and the latter suits better for the multipath fading channel environment whose channel frequency response (CFR) fluctuates rapidly with time. In the lattice-type structure, the estimation of the CFR makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time-and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. All interpolation schemes should rely on the pilot estimates only, and thus, their performances are bounded by the quality of pilot estimates. However, the additive noise give rise to high fluctuation on the pilot estimates, especially in a communication environment with low signal-to-noise ratio. These high fluctuations could be monitored in the alternating high values of the first forward differences (FFD) between pilot estimates. In this paper, we analyzed statistically those FFD values and propose a postprocessing algorithm to suppress high fluctuations in the noisy pilot estimates. The proposed method is based on a localized adaptive moving-average filtering. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification. It is shown that the mean-squared error (MSE) between the actual CFR and pilot estimates could be reduced up to 68% from the noisy pilot estimates.

• The KIPS Transactions:PartC
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• v.13C no.3 s.106
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• pp.369-374
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• 2006

This paper related with the performance improvement of adaptive equalizer that is a based on the tricepstrum eqalization algorithm by using the received signal. Adaptive equalizer used for the improvement of communication performance, like as high speed, maintain of synchronization, BER, at the receive side in the environment of communication channel of the presence of the aditive noise, phase distortion and frequency selective fading, mainly. It's characteristics are nearly same as the inverse characterstics of the communication channel. In this paper, the TEA algorithm using the HOS and the 16-QAM which is 2-dimensional signaling method for being considered signal was used. For the precoding of 16-QAM singnal in the assignment of the signal costellation, Gray code was used, and the improvement of performance was gained by computer simulation in the residual intersymbol interence and mean squared error which is representive measurement of adaptive equalizer.