• 대한전기학회논문지:시스템및제어부문D
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• 제51권8호
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.128-130
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• 1997

In the paper a problem of search for a moving robot by another moving robot is considered. The problem is formalized as minmax and maxmin task also as a game.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 1998년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Spring 1998
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• pp.413-420
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• 1998

In this paper, two methods, Stepp's and EQHAZARD, are introduced and applied to a recent earthquake catalog for the entire Korean Peninsula that can estimate the seismicity by incorporating the incompleteness of the earthquake catalog. EQHAZARD method, different from Stepp's method in that it used priori information besides the assumption of stationary Poisson process of the earthquakes, produces the higher seismicity rate for the smaller earthquakes. EQHAZARD method are also used to estimated the incompleteness of the recent earthquake catalog for the southern part of the Korean Peninsula in terms of the Probability of Activity for the specified earthquke magnitude classes and time periods. It is believed that the Probability of Activity thus obtained can be used as a strong priori information in estimating the seismicity for a seismic source within the region where there are not enough earthquakes detected. Finally, it is demonstrated that the arbitrary selection of the methods. of incompleteness analysis brings quite different seismic hazard results, which suggests the need to employ a rigid quantitative method for incompleteness analysis in estimating the seismicity parameters in order to reduce the uncertainty in the Seismic Hazard Results with the EQHAZARD method being one of the competent practical alternatives.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.591-594
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• 2008

This paper explores how to characterise security properties of software components, and how to reason about their suitability for a trustworthy compositional contract. Our framework provides an explicit opportunity for software composers as well as software components to test a priori security properties of software components in a system composition. The proposed framework uses logic programming as a tool to represent security properties of atomic components and reason about their compositional matching with other components.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.689-692
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• 1998

Matching two images is an essential step for many computer vision applications. A new approach to the scale and rotation invariant scene matching is presented. A set of andidate parameters are hypthesized by mapping the angular difference and a new distance measure to the hough space and by detecting maximally consistent points. The proposed method is shown to be much faster than the conventinal one where the relaxation process is repeated until convergence, while providing robust matching performance, without a priori information on the geometrical transformation parameters.

• 한국정보통신학회논문지
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• 제20권2호
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• pp.275-280
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• 2016

본 논문은 버퍼가 장착된 복수개의 중계기가 존재하는 연쇄적 데이터 중계 네트워크에서 각 중계기가 이미 복호에 성공한 정보를 활용하여 인접 중계기로부터의 간섭을 원천적으로 제거하는 새로운 중계 기법을 제안한다. 기존의 버퍼기반 중계 선택기술에서는 송신단으로부터 데이터를 수신할 중계기와 수신단으로 데이터를 전송할 중계기를 각각 하나씩 선택한다. 그러나 제안된 중계 기법에서는 수신단으로 데이터를 전송할 중계기가 선택된 후 나머지 모든 중계기들은 송신단으로부터 도착한 신호의 복호를 시도하고 복호에 성공한 모든 중계기들은 자신의 버퍼에 복호된 신호를 저장한다. 제안된 기법에서는 자신이 데이터를 전송했을 때, 자신의 신호가 수신단에 성공적으로 도착하면서 동시에 송신단으로부터 도착한 신호 복호에 성공하는 중계기의 수를 최대화하는 중계기가 선택된다. 컴퓨터 시뮬레이션을 통하여 제안된 중계기 선택 방식이 기존 중계기 선택 기법에 비해 훨씬 더 좋은 성능을 보이는 것을 확인한다.

• 한국지능시스템학회논문지
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• 제1권3호
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• pp.4-19
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• 1991

In this paper, we propose a fuzzy neural network pattern classifier utilizing fuzzy information. This system works without any a priori information about the number of clusters or cluster centers. It classifies each input according to the distance between the weights and the normalized input using Bezdek's [1] fuzzy membership value equation. This model returns the correct membership value for each input vector and find several cluster centers. Some experimental studies of comparison with other algorithms will be presented for sample data sets.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 정기총회 및 창립40주년기념 학술대회 학회본부
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• pp.73-75
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• 1987

The paper proposes a class of discrete-time adaptive controller which may be applicable without sufficient a priori information. Against choices of the Information, GPC algorithm may seem to be more robust than any other methods reported, but it is the method based on Indirect approach. It is, therefore, reasonable to propose an algorithm via the zero-gain prediction, in which the control parameters are directly estimated and calculated.

• Journal of Communications and Networks
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• 제11권2호
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.