• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.48 no.2
• /
• pp.21-28
• /
• 2011

We consider an RFID network configured as a star in which tags stationarily move into and out of the vicinity of the reader. To cognize the neighboring tags in the RFID network, we propose a scheme based on dynamic framed and slotted ALOHA which determines the number of slots belonging to a frame in a dynamic fashion. The tag cognizance scheme distinctively employs a rule for estimating the expected number of neighboring tags, identified as R-retrospective maximum likelihood rule, where the observations attained in the R previous frames are used in maximizing the likelihood of expected number of tags. Simulation result shows that a slight increase in depth of retrospect is able to significantly improve the cognizance performance.

• Journal of information and communication convergence engineering
• /
• v.13 no.3
• /
• pp.152-158
• /
• 2015

We consider the problem of designing independently operating local quantizers at nodes in distributed estimation systems, where many spatially distributed sensor nodes measure a parameter of interest, quantize these measurements, and send the quantized data to a fusion node, which conducts the parameter estimation. Motivated by the discussion that the estimation accuracy can be improved by using the quantized data with a high probability of occurrence, we propose an iterative algorithm with a simple design rule that produces quantizers by searching boundary values with an increased likelihood. We prove that this design rule generates a considerably reduced interval for finding the next boundary values, yielding a low design complexity. We demonstrate through extensive simulations that the proposed algorithm achieves a significant performance gain with respect to traditional quantizer designs. A comparison with the recently published novel algorithms further illustrates the benefit of the proposed technique in terms of performance and design complexity.

• The Journal of the Acoustical Society of Korea
• /
• v.29 no.1
• /
• pp.76-81
• /
• 2010

In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the second-order conditional maximum a posteriori (CMAP). In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the current observation and the speech activity decisions in the pervious two frames. Experimental results show that the proposed approach yields better results compared to the statistical model-based and the CMAP-based VAD using the LR test.

• Journal of the Korean Statistical Society
• /
• v.31 no.2
• /
• pp.229-235
• /
• 2002

A generalized Stein-rule estimator of the vector of regression coefficients in linear regression model is considered and its properties are analyzed according to the criterion of Pitman nearness. A comparative study shows that the generalized Stein-rule estimator representing a class of estimators contains particular members which are better than the usual Stein-rule estimator according to the Pitman closeness.

• Journal of the Korean Statistical Society
• /
• v.27 no.3
• /
• pp.251-264
• /
• 1998

When the LRT is not feasible, we define quasi-LRT(QLRT) as a modification of the LRT Under some appropriate conditions the QLRT shares Bahadur optimality and Bartlett Adjustability with the LRT. When we can find maximum likelihood estimator under the null parameter space but not under the unrestricted parameter space, our QLRT is Bahadur optimal as is the LRT We suggest the stopping rule of the Newton-Raphson iterations for constructing the QLRT statistics which are Bartlett adjustable.

• Journal of the Korean Statistical Society
• /
• v.23 no.1
• /
• pp.63-78
• /
• 1994

For discrimination with binary variables, reformulated full and first order Bahadur model with incomplete observations are presented. This allows prior probabilities associated with multiple population to be estimated for the sample-based classification rule. The EM algorithm is adopted to provided the maximum likelihood estimates of the parameters of interest. Some experiences with the models are evaluated and discussed.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.675-677
• /
• 2005

This study proposes a fuzzy classification using EM algorithm. For cluster validation, this approach iteratively estimates the class-parameters in the fuzzy training for the sample classes and continuously computes the log-likelihood ratio of two consecutive class-numbers. The maximum ratio rule is applied to determine the optimal number of classes.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.16 no.5
• /
• pp.104-111
• /
• 2002

This paper presents a fuzzy rule extraction method using EM(Expectation-Maximization) algorithm and a design method of adaptive neuro-fuzzy control. EM algorithm is used to estimate a maximum likelihood of a GMM(Gaussian Mixture Model) and cluster centers. The estimated clusters is used to automatically construct the fuzzy rules and membership functions for ANFIS(Adaptive Neuro-Fuzzy Inference System). Finally, we applied the proposed method to the water temperature control system and obtained better results with respect to the number of rules and SAE(Sum of Absolute Error) than previous techniques such as conventional fuzzy controller.

• East Asian Economic Review
• /
• v.23 no.4
• /
• pp.409-427
• /
• 2019

This paper sets up a new Keynesian model with external habit to explore the role of each shock over business cycles in Korea. The estimated model via maximum likelihood shows that the productivity shock plays a pivotal role in explaining the output variations before and after the financial crisis since mid-1970s. It also shows that the model with external habit is more successful in explaining the business cycles in Korea after the Asian financial crisis than the model without habit. The monetary policy shock which dominates by accounting for more than 70 percent of the unconditional variance of the inflation rate before the financial crisis is less important in the inflation rate fluctuations after the financial crisis. This partly reflects the regime change of the monetary policy to the inflation targeting rule after the financial crisis.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.5
• /
• pp.643-649
• /
• 1993

The problem of locating a periodically inserted frame synchronization pattern in random data for a binary pulse amplitude modulated (PAM) digital communication system over a additive white Gaussian noise(AWGN) channel with co-channel interference is considered. The performance degradation of frame synchronization for the correlation rule due to the presence of co-channel interference is shown. The maximum likelihood(ML) decision rule for the frame synchronization over an AWGN channel with co-channel interference is derived. For the entire range of SNR considered, the ML frame synchronization rule obtains about 1dB signal energy gain over the correlation rule. Specially, the ML rule obtains as much as 2dB gain over the correlation rule when the SNR is greater than 0dB.