• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.60-66
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• 1997

In this paper, a moving object surveillance system, which can extract moving object in real-time, using image subtraction method is described. This technique based on the novelty filter having the structure of neural network associative memory. Digital arithmetic and timing control parts were composed of hardwired controller to treat two-dimensional massive image information. SRAMS having 20 ns access time were used for the image buffer that has high speed write/read property. Image extraction algorithm is discussed and supported by simulation and experiments.

• Journal of the Korean Mathematical Society
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• v.48 no.2
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• pp.223-240
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• 2011

In this paper, the problem on periodic solutions of the bidirectional associative memory neural networks with both periodic coefficients and periodic time-varying delays is discussed. By using degree theory, inequality technique and Lyapunov functional, we establish the existence, uniqueness, and global asymptotic stability of a periodic solution. The obtained results of stability are less restrictive than previously known criteria, and the hypotheses for the boundedness and monotonicity on the activation functions are removed.

• 전기의세계
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• v.38 no.2
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• pp.39-52
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• 1989

본고에서는 우선 미국에서의 Neural Chip에 대한 개발현황에 대해서 고찰하고자 하며, 신경 세포를 실현하는데 어려운 문제점인 신경 세포간의 연결세기를 나타내는 어려운 문제점인 신경 세포간의 연결세기를 나타내는 Synapse를 구현하는 방법과 자극과 억제에 해당하는 입력 신호를 가해주는 방법에 대해서 소개하고자 한다. 그리고 국내 대학에서 연구한 결과로서 문자 인식을 하기 위한 영상처리의 전처리 과정인 잡음제거, 세선화, 특징점 추출에 대해서 신경회로망을 이용한 Chip 설계 방법과 4-bit A/D변환기, 4-bit가산기, 5 * 5 곱셈기, 그리고 Associative Memory를 VLSI로 구현하는 방법에 대해서 소개하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.87-95
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• 1997

This paper presents an optimal design procedure to realize an BSB neural networks by means of the parametrization of solution space and optimization of parameters using evaluation program. In particular, the performance index based on DOA analysis may make an associative memory implementation reach on the level of practical success.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.46-48
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• 1992

Through the last 20 years' study, it is a well-known fact that symbolic approach has limitations in generating a new concept from given concepts. Hence, neural networks having a role of associative memory based on dynamical activation of neurons attract AI scientists' attention. In this paper, recent trials for combining neural networks and Artificial Intelligent systems are systematically reviewed and a prototype ENEDB(Experimental Neuro Expert DataBase) system built on HP9000/300 workstation is introduced to show the possibility of using the trials for real applications.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.49.2-49
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• 2002

This paper describes the configuration of a multi-agent system that can recognize human intentions. This system constructs ontologies of human intentions and enables knowledge acquisition and sharing between intelligent agents operating in different environments. This is achieved by using a bi-directional associative memory network. The process of intention recognition is based on fuzzy association inferences. This paper shows the process of information sharing by using ontologies. The purpose of this research is to create human-centered systems that can provide a natural interface in their interaction with people.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.33-37
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• 1995

순환 신경회로망의 응용에서 종종 대두되는 국지극소점을 확인하고 제거하는 효과적인 방법을 제안한다. 신경망의 학습과정에서 밝혀지는 국지극소점에 대하여 부상관성을 부과하여 에너지표면을 재조정함으로서 원하는 상태에서 회로망이 안정에 도달하게 한다. 이때 의사상태(spurious states)는 안정조건을 적용함으로서 확인되는데 이과정은 특별히 설계된 병렬회로에 의하여 효율적으로 처리된다. 이와같은 부학습(unlearning)의 결과로서 순환신경망의 저장용량과 수렴성능의 개선을 이룰수 있다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.66-73
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• 1993

This paper presents an analog circuit implementation and experimental resuls of the Hopfield type neural network. The proposed architecture enables the reconfiguration betwewn feedback and feedforward networks and employs new circuit designs for the weight supply and storage, analog multilier, nd current-voltage converter, in order to achieve area efficiency as well as function al versatility. The layout design of the eight-neuron neural network is tested as an associative memory to verify its applicability to real world.

• Journal of KIISE:Software and Applications
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• v.29 no.8
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• pp.565-572
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• 2002

학습과 추론을 위하여 유용한 방법으로 퍼지연상기억장치가 있다. 본 논문에서는 보다 효과적으로 추론결과를 유도하기 위하여 퍼지연상기억장치를 학습하는 단계에서 오류 역전파를 통하여 노드들 사이의 연결가중치를 재조정하는 방법과 퍼지규칙들을 간결화하는 방법을 제안한다. 제안된 방법은 비디오 데이타의 장면전환을 검출하는 분야에 적용하여 성능평가를 수행한다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.130-137
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• 1992

This paper presents the word recognition method using a neural-fuzzy pattern matching, in order to make a proper speech pattern for a spectrum sequence and to improve a recognition rate. In this method, a frequency variation is reduced by generating binary spectrum patterns through associative memory using a neural network, and a time variation is decreased by measuring the simillarity using a fuzzy pattern matching. For this method using binary spectrum patterns and logic algebraic operations to measure the simillarity, memory capacity and computation requirements are far less than those of DTW using a conventional distortion measure. To show the validity of the recognition performance for this method, word recognition experiments are carried out using 28 DDD city names and compared with DTW and a fuzzy pattern matching. The results show that our presented method is more excellent in the recognition performance than the other methods.