• Transactions on Control, Automation and Systems Engineering
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• 제1권2호
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• pp.99-105
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• 1999

This paper presents a fuzzy H$\infty$ filtering problem for a class of uncertain nonlinear systems with time-varying delayed states and unknown inital state on the basis of Takagi-Sugeno(T-S) fuzzy model. The nonlinear systems are represented by T-S fuzzy models, and the fuzzy control systems utilize the concept of the so-called parallel distributed compensation. Using a single quadraic Lyapunov function, the stability and L2 gain performance from the noise signals to the estimation error are discussed. Sufficient conditions for the existence of fuzzy H$\infty$ filters are given in terms of linear matrix inequalities (LMIs). The filtering gains can also be directly obtained from the solutions of LMIs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권3호
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• pp.161-165
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• 2009

Increase of multimedia information in Web requires a new method to manage and service multimedia documents efficiently. This paper proposes a conceptual object grouping method by fuzzy filtering, which is automatically constituted based on increase of multimedia documents. The proposed method composes subsumption relations between conceptual objects automatically using fuzzy filtering of the document objects that are extracted from domains. Grouping of such conceptual objects is regarded as subsumption relation which is decided by $\mu$-cut. This paper proposes $\mu$-cut, FAS(Fuzzy Average Similarity) and DSR(Direct Subsumption Relation) to decide fuzzy filtering, which groups related document objects easily. This paper used about 1,000 conceptual objects in the performance test of the proposed method. The simulation result showed that the proposed method had better retrieval performance than those for OGM(Optimistic Genealogy Method) and BGM(Balanced Genealogy Method).

• 한국산업융합학회 논문집
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• 제27권2_1호
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• pp.249-256
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• 2024

Traditional methods for monitoring targets rely heavily on probabilistic data association (PDA) or Kalman filtering. However, achieving optimal performance in a densely congested tracking environment proves challenging due to factors such as the complexities of measurement, mathematical simplification, and combined target detection for the tracking association problem. This article analyzes a target tracking problem through the lens of fuzzy logic theory, identifies the fuzzy rules that a fuzzy tracker employs, and designs the tracker utilizing fuzzy rules and Kalman filtering.

• 한국컴퓨터정보학회논문지
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• 제16권12호
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• pp.43-48
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• 2011

현재 영상 정보 개선을 위한 다양한 영상 필터링 알고리즘들이 제시되고 있으며, 그 중에서 기존의 퍼지 논리를 이용한 필터링 알고리즘은 다른 기존의 필터링 방식에서 잡음이 제거된 후에 블러링 효과와 잡음 제거율이 반비례하는 단점을 개선하기 위해서 퍼지 논리를 적용하였다. 그러나 기존의 퍼지 필터 방법은 그레이 영상의 단색 정보만을 잡음의 판단 기준으로 하였기 때문에 칼라 영상에서는 비효율적이다. 따라서 본 논문에서는 기존의 퍼지 논리를 이용한 필터링 알고리즘의 문제점을 개선하는 동시에 컬러 영상에 적용할 수 있는 퍼지 필터 알고리즘을 제안한다. 제시된 퍼지 필터 알고리즘은 영상의 RGB 컬러 정보를 각각의 R, G, B 채널 영상으로 분리하고, 각 채널 영상에 서 마스크가 위치한 기준 픽셀의 잡음 가능성 정도를 퍼지 논리에 적용하여 판단한다. 잡음 정도에 따라서 출력 영상의 화소값을 평균값 또는 중간값으로 결정한다. 제안된 방법을 잡음이 존재하는 칼라 영상에 적용한 결과, 단색 정보를 기준으로 처리하는 기존의 필터 방법에 비해서 효과적인 것을 확인하였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2004년도 추계학술대회
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• pp.203-210
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• 2004

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems - content-based recommending and collaborative filtering. Collaborative filtering recommender systems have been very successful in both information filtering domains and e-commerce domains, and many researchers have presented variations of collaborative filtering to increase its performance. However, the current research on recommendation has paid little attention to the use of time related data in the recommendation process. Up to now there has not been any study on collaborative filtering to reflect changes in user interest. This paper proposes dynamic fuzzy clustering algorithm and apply it to collaborative filtering algorithm for dynamic recommendations. The proposed methodology detects changes in customer behavior using the customer data at different periods of time and improves the performance of recommendations using information on changes. The results of the evaluation experiment show the proposed model's improvement in making recommendations.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2008년도 정보통신설비 학술대회
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• pp.159-162
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• 2008

Generally, sensor nodes can be easily compromised and seized by an adversary because sensor nodes are hostile environments after dissemination. An adversary may be various security attacks into the networks using compromised node. False data injection attack using compromised node, it may not only cause false alarms, but also the depletion of the severe amount of energy waste. Dynamic en-route scheme for Filtering False Data Injection (DEF) can detect and drop such forged report during the forwarding process. In this scheme, each forwarding nodes verify reports using a regular probability. In this paper, we propose verification probability adjustment scheme of forwarding nodes though a fuzzy rule-base system for the Dynamic en-route filtering scheme for Filtering False Data Injection in sensor networks. Verification probability determination of forwarding nodes use false traffic rate and distance form source to base station.

• 한국컴퓨터정보학회논문지
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• 제17권11호
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• pp.27-32
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• 2012

본 논문에서는 기존의 퍼지 필터링 알고리즘의 문제점을 개선한 퍼지 필터링 기법을 제안한다. 제안된 퍼지 필터링 알고리즘은 컬러 영상에서 R, G, B 채널을 각각 분리한다. 분리된 각 채널에서 마스크 정보를 추출하여 채널에 대한 평균값과 중간값의 명암도를 제안된 퍼지 기법의 소속 함수에 적용하여 소속도를 구한 뒤, 추론 규칙에 적용한다. 그리고 R, G, B 각각의 소속도 값을 이용하여 잡음 가능성 여부를 판별한다. 제안된 퍼지 기법에서 소속 함수구간은 세 개 구간으로 설정하였다. 잡음이라고 판단되는 경우에는 그 잡음 정도에 따라 중간값이나 평균값을 해당 픽셀 값으로 설정하여 잡음을 제거한다. 제안된 기법을 컬러 영상에 적용한 결과, 제안된 기법이 기존의 퍼지 필터링 기법보다 잡음 제거에 있어서 효과적인 것을 확인할 수 있었다.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.461-464
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• 2007

In this paper, we propose a fuzzy Kalman filtering to deal with a estimation error covariance. The T-S fuzzy model structure is further rearranged to give a set of linear model using standard Kalman filter theory. And then, to minimize the estimation error covariance, which is inferred using the fuzzy system. It can be used to find the exact Kalman gain. We utilize the genetic algorithm for optimizing fuzzy system. The proposed state estimator is demonstrated on a truck-trailer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.206-209
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• 1999

Conventional target tracking techniques are primarily based on Kalman filtering or probabilistic data association(PDA). But it is difficult to perform well under a high cluttered tracking environment because of the difficulty of measurement, the problem of mathematical simplification and the difficulty of combined target detection for tracking association problem. This paper deals with an analysis of target tracking problem using fuzzy-logic theory, and determines fuzzy rules used by a fuzzy tracker, and designs the fuzzy tracker by using fuzzy rules and Kalman filtering.