• Journal of applied mathematics & informatics
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• 제29권1_2호
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• pp.211-225
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• 2011

In this paper, a class of bi-directional associative memory (BAM) fuzzy cellular neural networks with distributed delays and impulses is formulated and investigated. By employing an integro-differential inequality with impulsive initial conditions and the topological degree theory, some sufficient conditions ensuring the existence and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on the delay kernel functions and system parameters. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.

• 한국컴퓨터정보학회논문지
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• 제12권2호
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• pp.53-62
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• 2007

본 논문에서는 영상 에지 검출에 있어서 명암차에 의해 불분명한 경계 부분을 강건하게 하고, 방향성에 덜 민감한 에지 검출 알고리즘인 퍼지 웨이브렛 형태학 신경망을 제안한다. 이는 복잡하고 많은 연산 수행하는 단점을 극복하기 위해 DTCNN 구조에 데이터의 손실없이 강건하게 영상 단순화가 가능한 퍼지 웨이브렛 형태학 연산자를 적용한다. 또한 컬러 영상에서 효과적으로 에지 경계면의 특징 정보를 손실없이 가지고 있는 Y 영상을 YCbCr 공간 컬러 모델을 이용하여 분할 한다. 본 논문은 제안된 알고리즘의 성능검증을 위해 50개의 컬러 영상의 모의 실험을 제공한다.

• 대한안전경영과학회지
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• 제6권2호
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• pp.187-197
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• 2004

The recycling cell formation problem means that disposal products are classified into recycling product families using group technology in their end-of-life phase. Disposal products have the uncertainties of product condition usage influences. Recycling cells are formed considering design, process and usage attributes. In this paper, a new approach for the design of cellular recycling system is proposed, which deals with the recycling cell formation and assignment of identical products concurrently. Fuzzy ART neural networks are applied to describe the condition of disposal product with the membership functions and to make recycling cell formation. The approach leads to cluster materials, components, and subassemblies for reuse or recycling and can evaluate the value at each cell of disposal products. Disposal refrigerators are shown as an example.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(3)
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• pp.13-16
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• 2000

This paper is to compare DTCNN(Discrete-time Cellular Neural Networks) applying the fuzzy morphology operators with the conventional FCNN(Fuzzy CNN) using the general morphology operators. These methods are to the image filtering, and are compared as MSE. Also the main goal of this paper is to compare the fuzzy morphology operators with the general morphology operators through image input. In a result of computer simulation, we could know that the error of DTCNN applying the fuzzy morphology operators is less about 6.1809 than FCNN using the general morphology operators in the image included 10% noise, also the error of the former is less about 5.5922 than the latter in the image included 20% noise. And the image of DTCNN applying the fuzzy morphology operators is superior to FCNN using the general morphology operators.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.84-89
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• 2004

The machine cell formation problem is the problem to group machines into machine families and parts into part families so as to minimize bottleneck machines, exceptional parts, and inter-cell part movements in cellular manufacturing systems and flexible manufacturing systems. This paper proposes a new machine cell formation method based on the adaptive Hamming net which is a kind of neural network model. To show the applicability of the proposed method, it presents some experiment results and compares the method with other cell formation methods. From the experiments, we observed that the proposed method could produce good cells for the machine cell formation problem.