• 한국지능시스템학회논문지
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• 제16권1호
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• pp.24-29
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• 2006

연산기능을 갖는 새로운 진동성 신경회로를 설계하여 $0.5{\mu}m$ CMOS 공정으로 칩 제작을 하였다. 제안하는 진동성 신경회로는 흥분성 시냅스를 가진 3개의 신경진동자와 억제성 시냅스를 가진 1개의 신경진동자로 이루어진다. 사용된 진동자는 가변 부성저항과 트랜스콘덕터를 이용하여 설계하였다. 진동자의 입력단으로 사용되는 가변 부성저항은 가우시안 분포의 전류전압 특성을 지니는 범프 회로를 이용하여 구현하였다. 뉴럴 회로의 SPICE 모의실험결과 간단한 연산기능을 확인하였다. 제작된 칩을 ${\pm}$ 2.5 V 의 전원전압 조건에서 측정하였고 이를 모의실험결과와 비교 분석하였다.

• Applied Microscopy
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• 제46권4호
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• pp.176-178
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• 2016

Efficient neural circuit reconstruction requires sufficient lateral and axial resolution to resolve individual synapses and map a large enough volume of brain tissue to reveal the molecular identity and origin of these synapses. Sparse circuit reconstruction using array tomography meets many of these requirements but also has some limitations. In this minireview, the advantages and disadvantages of applicable imaging techniques will be discussed.

• Applied Microscopy
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• 제51권
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• pp.9.1-9.10
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• 2021

Brain disorders seriously affect life quality. Therefore, non-invasive neuroimaging has received attention to monitoring and early diagnosing neural disorders to prevent their progress to a severe level. This short review briefly describes the current MRI and PET/CT techniques developed for non-invasive neuroimaging and the future direction of optical imaging techniques to achieve higher resolution and specificity using the second near-infrared (NIR-II) region of wavelength with organic molecules.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.569-572
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• 1992

This paper describes a new method of pseudorandom testing of a digital circuit by use of correlation method and a neural network. The authors have recently proposed a new method of fault diagnosis of logical circuit by applying a pseudorandom M-sequence to the circuit under test, calculating the crosscorrelation function between the input and the output, and comparing the crosscorrelation functions with the references. This method, called MSEC method, is further extended by using a neural network in order to not only detect the existence of faults but also find the place or location of the faults. An experiment by using a simple digital circuit shows enough applicability of this method to industrial testing of circuit board.

• 센서학회지
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• 제12권1호
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• pp.51-56
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• 2003

We describe a charge pump circuit using VCO (voltage controlled oscillator) for storing information into local memories in neural networks. The VCO is used for adjusting the output voltage of the charge pump to the reference voltage and for reducing the fluctuation generated by the clocking scheme. The charge pump circuit is simulated by using Hynix 0.35um CMOS process parameters. The proposed charge pump operates properly regardless to the temperature and the supply voltage variation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.103-106
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• 2003

An oscillatory neural network circuit has been designed and fabricated in an 0.5 ${\mu}{\textrm}{m}$ double poly CMOS technology. The proposed oscillatory neural network consists of 3 neural oscillator cells with excitatory synapses and a neural oscillator cell with inhibitory synapse. Simulations of a network of oscillators demonstrate cooperative computation. Measurements of the fabricated chip in condition of $\pm$ 2.5 V power supply is shown.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제11B권2호
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• pp.15-21
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• 2001

This paper presents an improved characteristic analysis methodology for a 5-phase hybrid stepping motor. The basic approach is based on the use of equivalent magnetic circuit taking into account the localized saturation throughout the hybrid stepping motor. The finite element method(FEM) is used to generate the magnetic circuit parameters for the complex stator and rotor teeth and airgap considering the saturation effects in tooth and poles. In addition, the neural network is used to map a change of parameters and predicts their approximation. Therefore, the proposed method efficiently improves the accuracy of analysis by using the parameter characterizing localized saturation effects and reduces the computational time by using the neural network. An improved circuit model of 5-phase hybrid stepping motor is presented and its application is provided to demonstrate the effectiveness of the proposed method.

• Applied Microscopy
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• 제46권4호
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• pp.171-175
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• 2016

A distinctive neuronal network in the brain is believed to make us unique individuals. Electron microscopy is a valuable tool for examining ultrastructural characteristics of neurons, synapses, and subcellular organelles. A recent technological breakthrough in volume electron microscopy allows large-scale circuit reconstruction of the nervous system with unprecedented detail. Serial-section electron microscopy-previously the domain of specialists-became automated with the advent of innovative systems such as the focused ion beam and serial block-face scanning electron microscopes and the automated tape-collecting ultramicrotome. Further advances in microscopic design and instrumentation are also available, which allow the reconstruction of unprecedentedly large volumes of brain tissue at high speed. The recent introduction of correlative light and electron microscopy will help to identify specific neural circuits associated with behavioral characteristics and revolutionize our understanding of how the brain works.

• 한국경영과학회지
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• 제17권1호
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• pp.3-16
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• 1992

We present a modified Tank and Hopfield's neural network model for solving Linear Programming problems. We have found the fact that the Tank and Hopfield's neural circuit for solving Linear Programming problems has some difficulties in guaranteeing convergence, and obtaining both the primal and dual optimum solutions from the output of the circuit. We have identified the exact conditions in which the circuit stops at an interior point of the feasible region, and therefore fails to converge. Also, proper scaling of the problem parameters is required, in order to obtain a feasible solution from the circuit. Even after one was successful in getting a primal optimum solution, the output of the circuit must be processed further to obtain a dual optimum solution. The modified model being proposed in the paper is designed to overcome such difficulties. We describe the modified model and summarize our computational experiment.

• 전자공학회논문지SC
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• 제40권4호
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• pp.275-281
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• 2003

0.5㎛ 2중 폴리 CMOS 공정을 이용하여 새로운 뉴럴 오실레이터를 설계, 제작하였다. 제안하는 뉴럴 오실레이터는 트랜스콘덕터 및 캐패시터와 비선형 가변 부성저항으로 이루어진다. 뉴럴 오실레이터의 입력단으로 사용되는 비선형 가변 부성저항은 정귀환의 트랜스콘덕터와 가우시안 분포의 전류전압 특성을 지니는 범프 회로를 이용하여 구현하였다. 또한 SPICE 모의실험을 통하여 제안한 오실레이터의 특성분석 후 집적회로 설계를 실시하였다. 한편 흥분성 및 억제성 시냅스로 연결된 4개의 뉴럴 오실레이터로 간단한 신경회로망을 구성하여 그 특성을 확인하였다. 집적회로로 제작된 뉴럴 오실레이터에 대하여 ± 2.5 V 전원 조건하에서 측정된 결과를 분석하고 모의실험 결과와 비교한다.