• 생물정신의학
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• 제18권2호
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• pp.55-60
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• 2011

Neuroimaging studies in schizophrenia have remarkably increased and provided some clues to understand its pathophysiology. Here, we reviewed the neuroimaging, studies including volume analysis, functional magnetic resonance imaging (MRI) and diffusion tensor imaging, and findings in both early stage schizophrenia and high-risk group. The reviewed studies suggested that the brain with schizophrenia showed both regional deficits and dysconnectivity of neural circuit in the first episode, even high-risk group as well as chronic schizophrenia. Multimodal neuroimaging or combined approach with genetic, electro-or magneto-encephalographic data could provide promising results to understand schizophrenia in the near future.

• Fisheries and Aquatic Sciences
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• 제10권3호
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• pp.159-169
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• 2007

The complex 2-dimensional movements of fish during an annual migration circuit were generated and simulated by a chaotic model of fish movement, which was expanded from a small-scale movement model. Fish migration was modeled as a neural network including stimuli, central decision-making, and output responses as variables. The input stimuli included physical stimuli (temperature, salinity, turbidity, flow), biotic factors (prey, predators, life cycle) and landmarks or navigational aids (sun, moon, weather), values of which were all normalized as ratios. By varying the amplitude and period coefficients of the klinokinesis index using chaotic equations, model results (i.e., spatial orientation patterns of migration through time) were represented as fish feeding, spawning, overwintering, and sheltering. Simulations using this model generated 2-dimesional annual movements of sea bream migration in the southern and western seas of the Korean Peninsula. This model of object-oriented and large-scale fish migration produced complicated and sensitive migratory movements by varying both the klinokinesis coefficients (e.g., the amplitude and period of the physiological month) and the angular variables within chaotic equations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.468-468
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• 2000

In our laboratory, the control aspects are investigated in the photovoltaic power generation systems (PV systems). The PV system is very good for earth environment, but if it connects to power network system, many problems are raised (protection, voltage, harmonics etc.). In this paper, we present the result of the basic studies for the building of the PV system that amplifies the electric energy obtained from the solar cell. We consider electronic circuits in order to protect the PV system from power surge induced by lightning and also design an electronic circuit in order to detect defaults in the power network system. We would like to integrate these circuits into the PV system by considering its control equipment build by 8-bit microcomputer using various control theory (fuzzy, neural network etc.).

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1996년도 추계학술대회 논문집
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• pp.1-4
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• 1996

EEPROM technology has been used for storing analog weights as charge in a nitride layer between gate and channel of a field effect transistor. In the view of integrity and fabrication process, it is essentially required that SONOSFET is capable of performing synapse function as a basic element in an artificial neural networks. This work has introduced the VLSI implementation for synapses including current study and also investigated physical characteristics to implement synapse circuit using SONOSFET memories. Simulation results are shown in this work. It is proposed that multiplication of synapse element using SONOSFET memories will be developed more compact implementation under Present fabrication processes.

• 한국레이저가공학회지
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• 제3권3호
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• pp.13-19
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• 2000

The stencil is a thin stainless sheet in which a pattern is formed, which is placed on a surface of plate to reproduce the pattern of electric circuit. Conventionally the stencil has been produced by etching process. This process has many anti-environmental factors. In this study, Nd : YAG laser cutting process has been applied for stencil manufacturing. The study is focused on estimating kerf width of laser cut stencil by E.B.P.(Error Back-Propagation). This algorithm is good for estimating target value from input value. In this paper, target value was kerf width, and input values were frequency, pulse width, cutting speed and laser power. E.B.P. after teaming input and target could estimate kerf width from some variables precisely.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.325-326
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• 2018

본 논문에서는 PCB 공정상의 육안검사를 통한 불량 분류 방식에서 CNN을 이용한 PCB 불량 분류 방식을 제안한다. 이 방식은 육안검사의 문제점인 작업자의 숙련도에 따른 검사 효율을 자동화 검사 시스템에 의해 해결하며, 불량 위치와 종류를 결과 이미지에 표시한다. 또한 이미지 분류 결과를 모니터링할 수 있도록 시리얼 통신을 통하여 Darknet 프레임워크와 LCD를 연동하였다. 적은 량의 데이터 셋으로도 좋은 결과를 냈으며, 다양한 데이터 셋을 이용해 훈련할 시 전반적인 PCB 불량의 분류가 가능할 것으로 예상된다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.701-704
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• 2001

최근 카오스현상에 대한 연구가 지속적으로 이루어지고 있다 카오스 철상을 이용하여 많은 분야에서 다양하게 연구되고 있는바 본 논문에서는 1차원 CNN을 구성하여 하이퍼카오스 신호를 생성하고 하이퍼카오스 동기화에 기반을 둔 암호화 통신을 적용하여 구현하는데 초점을 맞추었다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.705-708
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• 2001

최근 카오스현상에 대한 연구가 지속적으로 이루어지고 있다. 카오스 현상을 이용하여 많은 분야에서 다양하게 연구되고 많은 응용기술이 개발되고 있다. 본 논문에서는 1차원 CNN을 구성하여 하이퍼카오스 신호를 생성하고 하이퍼카오스 동기화 구현하는데 초점을 맞추었다.

• 전자공학회논문지B
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• 제33B권9호
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• pp.107-116
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• 1996

In the stochastic structure for doing exact calculationk, an input number must be changed to a pulse stream. Because the performance of random number generator (RNG) is controlled by its initial condition, we suggested newly modified cellular automata (MCA) which is uses a counter for boundary condition. We compared newly suggested MCA RNG to previously reported RNGs using the AND gate passing outputs which have the same meaning of multiplication in the stochastic calculation. In order to use stochastic we studied about the method, one large RNG can generate many small random numbers. In this method, RNG must have large drive capabilities for many input comparator. So we studied about drive capabilities using BiCMOS circuit and CMOS circit by SPICE.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2977-2979
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• 1999

본 논문에서는 MEBP(Modified Error Back-Propagation) 학습 규칙을 간단한 비선형 회로를 이용하여 구현하였다. 인공 신경 회로망(ANNs : Artificial Neural Networks)은 많은 수의 뉴런을 필요하기 때문에 표준 CMOS 기술을 이용하는 간단한 비선형 시냅스(synapse) 회로는 인공 신경 회로망 구현에 적합하다. 학습회로는 비선형 시냅스 회로. 시그모이드(sigmoid) 회로. 그리고 선형 곱셈기로 구성되어 있다. 학습 회로의 출력은 각 입력 패턴에 따라 유일한 값으로 결정되어진다. 제안한 학술회로를 $2{\times}2{\times}1$과 $2{\times}3{\times}1$ 다층 feedforward 신경 회로망 모델에 적용하였다. MEBP 하드웨어 구현은 HSPICE 회로 시뮬레이터를 이용하여 검증하였다. 제안한 학술 회로는 on-chip 학습회로를 포함한 대규모 신경회로망 구현에 매우 적합하리라 예상된다.