• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.97-103
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• 2012

A very low complexity QRD-M algorithm based on limited search area is proposed for MIMO systems. The conventional QRD-M algorithm calculates Euclidean distance between all constellation symbols and the temporary detection symbol at each layer. We found that performance will not be degraded even if we adaptively restrict the search area of the candidate symbols only to the neighboring points of temporary detection symbol according to the channel condition at each layer. As a channel condition indicator, we employ the channel gain ratio among the layers without necessity of SNR estimation. The simulation results show that the proposed scheme effectively achieves near optimal performance while maintaining the overall average computation complexity much smaller than the conventional QRD-M algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.3
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• pp.195-202
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• 2015

NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on exponential power distribution software reliability model finite failures and infinite failures were presented for comparison problem. As a result, finite fault model is effectively infinite fault models, respectively. The parameters estimation using maximum likelihood estimation was conducted. In this research, software developers to identify software failure property some extent be able to help is considered.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.3009-3015
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• 2013

Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer and method of the most fundamental being determining an individual's genotype from multiple aligned short read sequences at a position. Bayesian algorithm estimate parameter using posterior genotype probabilities and other method, EM algorithm, estimate parameter using maximum likelihood estimate method in observed data. Here, we propose a novel genotype-calling system and compare and analyze the effect of sample size(S = 50, 100 and 500) on posterior estimate of sequencing error rate, somatic mutation status and genotype probability. The result is that estimate applying Bayesian algorithm even for 50 of small sample size approached real parameter than estimate applying EM algorithm in small sample more accurately.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.245-254
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• 2004

This paper deals with the problem of estimating structure and motion from long continuous image sequences, applying the Expectation Maximization algorithm based on extended Kalman smoother to impose the time-continuity of the motion parameters. By repeatedly estimating the state transition matrix of the dynamic equation and the parameters of noise processes in the dynamic and measurement equations, this optimization gives the maximum likelihood estimates of the motion and structure parameters. Practically, this research is essential for dealing with a long video-rate image sequence with partially unknown system equation and noise. The algorithm is implemented and tested for a real image sequence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1903-1910
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• 2009

In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used the Weibull distribution which has the efficient various property which has the place efficient quality. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.646-652
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• 2014

It is the primary aim of this paper to propose the empirical fatigue crack propagation model fit to describe a crack growth behavior of AZ31 magnesium alloys under the different specimen thickness conditions. The empirical models estimated are Paris-Erdogan model, Walker model, Forman model, and modified-Forman model. The parameters of each model are estimated by maximum likelihood method. The statistical crack growth data needed for an estimation of empirical models are obtained by fatigue crack propagation tests under the three cases of specimen thickness. It is found that the good empirical models fit to describe a crack growth behavior of AZ31 magnesium alloys under the different specimen thickness conditions are Paris-Erdogan model and Walker model. It is also verified that a fatigue crack growth rate exponent of a empirical model may be a material constant at the specimen thickness conditions of 4.75mm and 6.60mm.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.708-708
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• 2002

Recent developments in sensor technologies have provided remotely sensed data with very high spatial resolution. In order to fully utilize the potential of high resolution images, new image classification strategies are necessary. Unfortunately, the high resolution images increase the spectral within-field variability, and the classification accuracy of traditional methods based on pixel-based classification algorithms such as Maximum-Likelihood method may be decreased (Schiewe 2001). Recent development in Object Oriented Classification based on image segmentation algorithms can be used for the classification of forest patches on rugged terrain of Korea. The objectives of this paper are as follows. First, to compare the pros and cons of image classification methods based on pixel-based and object oriented classification algorithm for the forest patch classification. Landsat ETM＋ data and IKONOS data will be used for the classification. Second, to investigate ways to increase classification accuracy of forest patches. Supplemental data such as DTM and Forest Type Map of 1:25,000 scale are used for topographic correction and image segmentation. Third, to propose the best classification strategy for forest patch classification in terms of accuracy and data requirement. The research site for this paper is Namhansansung Provincial Park located at the eastern suburb of Seoul Metropolitan City for its diverse forest patch types and data availability. Both Landsat ETM＋ and IKONOS data are used for the classification. Preliminary results can be summarized as follows. First, topographic correction of reflectance is essential for the classification of forest patches on rugged terrain. Second, object oriented classification of IKONOS data enables higher classification accuracy compared to Landsat ETM＋ and pixel-based classification. Third, multi-stage segmentation is very useful to investigate landscape ecological aspect of forest communities of Korea.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1601-1605
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• 2004

When codeword sequence has two or less successive transitions, the performance of 4th-order partial response maximum-likelihood (PRML) detector can be improved. However, the code leads to an unacceptable loss of performance due to the low code rate. For a rate 718 code that MTR constraint (i) of each codeword is limited to 2, and j is allowed to be 3 when codewords are connected, we modified the trellis of PRML detector to combine j=2 with J=3. We confirmed that the rate 718 coded 4th-order PRML detection with combined trellis achieves the SNR gain more than 2dB compared to the rate 819 coded 4u_order PRML detection at 10-s BER in high-density longitudinal or perpendicular magnetic recording systems.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.341-353
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• 1993

As an estimator of the conditional probability of discovering a new species at the next observation after a sample of certain size is taken, the one proposed by Good(1953) has been most widely used. Recently, Clayton and Frees(1987) showed via simulation that their nonparametric maximum likelihood estimator(NPMLE) has smaller MSE than Good's estimator when the population is relatively nonuniform. Lee(1989) proved that their conjecture is asymptotically true for truncated geometric population distributions. One shortcoming of the NPMLE, however, is that it has a considerable amount of negative bias. In this study we proposed a bias-corrected version of the NPMLE for virtually all realistic population distributions. We also showed that it has a smaller asymptotic MSE than Good's extimator except when the population is very uniform. A Monte Carlo simulation was performed for small sample sizes, and the result supports the asymptotic results.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.741-752
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• 2016

Numerous studies have shown that normal inverse Gaussian (NIG) distribution adequately fits the empirical return distribution of financial securities. The estimation of parameters can also be done relatively easily, which makes the NIG distribution more useful in financial markets. The maximum likelihood estimation and the method of moments estimation are easy to implement; however, we may encounter a problem in practice when a relationship among the moments is violated. In this paper, we investigate this problem in the parameter estimation and try to find a simple solution through simulations. We examine the effect of our adjusted estimation method with real data: daily log returns of KOSPI, S&P500, FTSE and HANG SENG. We also checked the performance of our method by computing the value at risk of daily log return data. The results show that our method improves the stability of parameter estimation, while it retains a comparable performance in goodness-of-fit.