• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.77-82
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• 2001

This paper deals with a fault detection algorithm for linear descriptor systems via unknown input PI observer. An unknown input PI observer is presented and its realization conditions is proposed by using the rank condition of system matrices. From the characteristics of unknown input PI observer, the states of system with unknown inputs are estimated and the occurrences of fault are detected, and its magnitudes are estimated easily by using integrated output estimation error under the step faults. Finally, a numerical example is given to verify the effectiveness of the proposed fault detection algorithm.

• 한국통신학회논문지
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• 제16권3호
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• pp.219-231
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• 1991

이 논문에서는 약한 신호 검파에 쉽게 쓰일 수 있는 국소 최적 검파의 여러 결과를 간략하게 소개하였다. 또한 국소 최적 검파의 바보수형 접근 방식인 국소 최적 순위 감파방지도 소개하였다. 이런 국소 최적 검파기들의 실제 응용 보기 및 구현에서의 분재, 성능 특징에 대해서도 알아보았다. 끝으로 일반화된 Neyman Pearson 정리를 피지 이론으로 확장한 정리를 간략히 소개하였다.

• 대한전자공학회논문지SP
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• 제37권1호
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• pp.76-82
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• 2000

이 논문에서는 먼저 약의존성을 나타내는 덧셈꼴 잡음환경을 잘 나타낼 수 있는 모형을 생각하였다 그 다음에 이 모형에서 순위 통계량을 바탕으로 하여 알려진 신호와 확률 신호의 비모수 검파를 생각하였다 약의존성 잡음모형에서 알려진 신호와 확률신호를 검파하는 국소최적순위검파기의 검정통계량을 얻었으며, 점근상대효율을 써서 이들 검파기의 성능을 분석하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.452-452
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• 2000

This paper deals with a fault detection algorithm for linear descriptor systems via unknown input PI observer. An unknown input PI observer is presented and its realization conditions is proposed by using the rank condition of system matrices. From the characteristics of unknown input PI observer, the states of system with unknown inputs are estimated and the magnitude of failures are detected and isolated easily by using integrated output error under the step failures. Finally, a numerical example is given to verify the effectiveness of the proposed algorithm.

• 정보과학회 논문지
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• 제45권1호
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• pp.15-21
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• 2018

낮은 계수 표현(Low-Rank Representation, LRR) 기반 방법은 얼굴 클러스터링, 객체 검출 등의 여러 실제 응용에 널리 사용되고 있다. 이 방법은 그래프 기반 준지도 학습에서 그래프 구축에 사용할 경우 높은 예측 정확도를 확보할 수 있어 많이 사용된다. 그러나 LRR 문제를 해결하기 위해서는 알고리즘의 매 반복마다 데이터 수 크기의 정방행렬에 대해 특이값 분해를 수행하여야 하므로 계산 비효율적이다. 이를 해결하기 위해 속도를 향상시킨 발전된 LRR 방법을 제안한다. 이는 최근 발표된 Fast LRR(FaLRR)을 기반으로 하며, FaLRR이 속도는 빠르지만 실제로 분류 문제에서 성능이 낮은 것을 해결하기 위해 기반 최적화 목표에 추가 제약 조건을 도입하고 이를 최적화하는 방법을 제안한다. 실험을 통하여 제안 방법은 LRR보다 더 좋은 해를 빠르게 찾아냄을 확인할 수 있다. 또한, 동일한 해를 도출하는 방법을 찾아내기는 어렵지만 최소화하는 목표가 추가될 경우 더 좋은 결과를 나타내는 Fast MLRR(FaMLRR)을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• 정보보호학회논문지
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• 제26권3호
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• pp.655-659
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• 2016

본 논문에서는 IPv6를 적용한 표준인 IEEE 802.15.4e와 RPL을 기반으로 하는 사물인터넷 환경에서 가용성을 확보하기 위하여 패킷 유실 공격 탐지 기법과 우회 기법을 제안한다. RPL의 순위값과 패킷 유실 연속성을 고려하여 패킷 유실 탐지 메트릭을 개선하였고 RPL을 통해 생성된 라우팅 경로에서 형제노드 및 자식노드를 활용한 우회기법을 구성하였다. 시뮬레이션을 통해 제안한 탐지 기법의 탐지 속도가 향상되었음을 확인하였고 제안한 우회 기법의 우회 성공률이 향상되었음을 확인하였다.

• ETRI Journal
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• 제32권3호
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• pp.490-492
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• 2010

This letter proposes a robust feature extraction method using a spatially normalized mean for temporal ordinal measurement. Before computing a rank matrix from the mean values of non-overlapped blocks, each block mean is normalized so that it obeys the invariance property against linear additive and subtractive noise effects and is insensitive against multiplied and divided noise effects. Then, the temporal ordinal measures of spatially normalized mean values are computed for the feature matching. The performance of the proposed method showed about 95% accuracy in both precision and recall rates on various distortion environments, which represents the 2.7% higher performance on average compared to the temporal ordinal measurement.

• KIEE International Transaction on Systems and Control
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• 제2D권2호
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• pp.115-119
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• 2002

In this paper we present a generalized directional morphological filtering algorithm for the removal of impulse noise, which is based on a combination of impulse noise detection and a weighted rank-order morphological filtering technique. For salt (or pepper) noise suppression, the generalized directional opening (or closing) filtering of the input signal is selectively used. The detection of impulse noise can be done by the geometrical difference of opening and closing filtering. Simulations show that this new filter has better detail feature preservation with effective noise reduction compared to other nonlinear filtering techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.421-433
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• 2015

Recently, there have been fast-growing social network services based on the Internet environment and web technology development, the prevalence of smartphones, etc. Social networks also allow the users to convey the information and news so that they have a great influence on the public opinion formed by social interaction among users as well as the spread of information. On the other hand, these social networks also serve as perfect environments for rampant malware. Malware is rapidly being spread because relationships are formed on trust among the users. In this paper, an effective patch strategy is proposed to deal with malicious worms based on social networks. A graph is formed to analyze the structure of a social network, and subgroups are formed in the graph for the distributed patch strategy. The weighted directions and activities between the nodes are taken into account to select reliable key nodes from the generated subgroups, and the Incremental PageRanking algorithm reflecting dynamic social network features (addition/deletion of users and links) is used for deriving the high influential key nodes. With the patch based on the derived key nodes, the proposed method can prevent worms from spreading over social networks.