• 충청수학회지
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• 제8권1호
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• pp.11-17
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• 1995

Let ${\tau}_a$ be the first time that a perturbed random walk with extended real-valued independent and identically distributed (i.i.d.) random variables crosses a constant boundary $a{\geq}0$. For the stopping times ${\tau}_a$ we investigate some basic properties and obtain its limiting distribution as $a{\rightarrow}{\infty}$ and an upper bound of the expected stopping times E(${\tau}_a$).

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.1049-1058
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• 2011

This paper suggests blending time adjusting method of braking command characteristics management and Set value test for optimizing of braking deceleration to enhance the precise position stopping. This method minimizes pneumatic-braking degree deviation by characteristics management, and secures braking stability at braking. By Set value test method, braking blending characteristics are analyzed accurately. And by optimal timing tuning at braking blending, It enhanced the precise position stopping with stabilization of deceleration To demonstrate the usefulness of these suggestion, I modeled for Deajeon Line #1. And through comparison with case of related companies, the proposed method which this paper suggested is proved to be superior to others.

• 정보통신설비학회논문지
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• 제8권4호
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• pp.207-215
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• 2009

In recent digital communication systems, the performance of Turbo Code used as the error correction coding method depends on the interleaver size influencing the free distance determination and iterative decoding algorithms of the turbo decoder. However, some iterations are needed to get a better performance, but these processes require large time delay. Recently, methods of reducing the number of iteration have been studied without degrading original performance. In this paper, the new method combining ME (Mean Estimate) stopping criterion with SDR (sign difference ratio) stopping criterion of previous stopping criteria is proposed, and the fact of compensating each method's missed detection is verified Faster decoding realizes that reducing the number of iterative decoding about 1~2 times by adopting our proposed method into serially concatenation of both decoder. System Environments were assumed DS-CDMA forward link system with intense MAI (multiple access interference).

• ETRI Journal
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• 제34권2호
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• pp.272-275
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• 2012

This letter studies the problem of exploiting multichannel diversity in a spectrum sharing system, where the secondary user (SU) sequentially explores channel state information on the licensed channels with time consumption. To maximize the expected achievable throughput for the SU, we formulate this problem as an optimal stopping problem, whose objective is to choose the right channel to stop exploration based on the observed signal-to-noise ratio sequence. Moreover, we propose a myopic but optimal rule, called one-stage look-ahead rule, to solve the stopping problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권10호
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• pp.3851-3866
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• 2015

The dynamic nature of opportunistic networks results in long delays, low rates of success for deliveries, etc. As such user experience is limited, and the further development of opportunistic networks is constrained. This paper proposes a prediction-based routing method for opportunistic networks (PB-OppNet). Firstly, using an ARIMA model, PB-OppNet describes the historical contact information between a node pair as a time series to predict the average encounter time interval of the node pair. Secondly, using an optimal stopping rule, PB-OppNet obtains a threshold for encounter time intervals as forwarding utility. Based on this threshold, a node can easily make decisions of stopping observing, or delivering messages when potential forwarding nodes enter its communication range. It can also report different encounter time intervals to the destination node. With the threshold, PB-OppNet can achieve a better compromise of forwarding utility and waiting delay, so that delivery delay is minimized. The simulation experiment result presented here shows that PB-OppNet is better than existing methods in prediction accuracy for links, delivery delays, delivery success rates, etc.

• Journal of information and communication convergence engineering
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• 제21권3호
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• pp.198-207
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• 2023

Responding to changes in artificial intelligence models and the data environment is crucial for increasing data-learning accuracy and inference stability of industrial applications. A learning model that is overfitted to specific training data leads to poor learning performance and a deterioration in flexibility. Therefore, an early stopping technique is used to stop learning at an appropriate time. However, this technique does not consider the homogeneity and independence of the data collected by heterogeneous nodes in a differential network environment, thus resulting in low learning accuracy and degradation of system performance. In this study, the generalization performance of neural networks is maximized, whereas the effect of the homogeneity of datasets is minimized by achieving an accuracy of 99.7%. This corresponds to a decrease in delay time by a factor of 2.33 and improvement in performance by a factor of 2.5 compared with the conventional method.

• Journal of the Korean Statistical Society
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• 제28권3호
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• pp.297-309
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• 1999

A sequential procedure of fixed-width confidence intervals for quantiles satisfying a condition of coverage probability is provided based on recursive density estimators. It is shown that the proposed sequential procedure is asymptotically efficient. In addition, the asymptotic normality for the proposed stopping time is derived.

• Journal of the Korean Statistical Society
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• 제26권3호
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• pp.309-317
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• 1997

A sequential procedure for estimating a linear function of two normal means which satisfies the two requirements, i.e. one is a condition of coverage probability, the other is a condition of $\beta$-protection, is proposed when the variances are unknown and not necessarily equal. We give asymptotic behaviors of the proposed stopping time.

• 대한전자공학회논문지SD
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• 제40권12호
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• pp.39-45
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• 2003

칩의 크기가 증가함에 따라 VHDL 모델의 설계검증은 점점 어려워지고, 많은 시간을 소모하는 과정이 되고 있다. 최근에 VHDL 모델을 검증하기 위하여 베이지안 예측과 정지법(stopping rule)을 이용한 방법들이 소개되고 있다. 이 논문에서는 VHDL 모델을 검증하기 위하여 정지법을 사용할 때 클럭 사이클을 줄일 수 있는 2가지 방법을 제안한다. 첫 번째 방법은 세미랜덤변수를 정의하고, 정지법이 동작 중에 세미랜덤변수의 영역에 존재하는 데이터를 생략하여 정지점stopping point)을 줄이고, 두 번째 방법은 정지법의 페이즈가 변화시에 베이지안 파라미터의 기존 값을 그대고 유지하여 클럭 사이클을 줄이는 방법이다. 제안된 방법의 효율성을 입증하기 위하여 12개의 VHDL 모델에 대하여 분기검출율에 관한 모의실험을 하였으며, 기존의 방법과 비교하여 분기검출율은 0.6% 줄었지만 25% 이상의 클럭 사이클을 줄일 수 있었다.

• 대한산업공학회지
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• 제29권2호
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• pp.165-171
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• 2003

Visual search in an unstructured search field is a fruitful research area for computational modeling. Search models that describe relationship between search time and probability of target detection have been used for prediction of human search performance and provision of ideal goals for search training. Until recently, however, most of models were focused on detecting a single target in a search field, although, in practice, a search field includes multiple targets and search models for multiple targets may differ from search models for a single target. This study proposed a random search model for multiple targets, generalizing a random search model for a single target which is the most typical search model. To test this model, human search data were collected and compared with the model. This model well predicted human performance in visual search for multiple targets. This paper also proposed how to determine optimal stopping time in multiple-target search.