• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.25-28
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• 2000

In this paper, an effective intention reading scheme is proposed for human-friendly interface. Soft computing techniques such as fuzzy logic and artificial neural networks are used for this. And Gabor filter based feature(GG feature) is also proposed to deal with local activity in the human face. It is based on human visual system and Gabor filter based approach is very popular in these days. The proposed scheme is adopted for human-friendly interface for rehabilitation service robotic system KARES II.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.149-158
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• 1996

In this paper we describe designing and implementing a digital neural chip and a parallel neural machine for simulating large scale neural netsorks. The chip is a single-chip multiprocessor which has four digiral neural processors (DNP-II) of the same architecture. Each DNP-II has program memory and data memory, and the chip operates in MIMD (multi-instruction, multi-data) parallel processor. The DNP-II has the instruction set tailored to neural computation. Which can be sed to effectively simulate various neural network models including on-chip learning. The DNP-II facilitates four-way data-driven communication supporting the extensibility of parallel systems. The parallel neural machine consists of a host computer, processor boards, a buffer board and an interface board. Each processor board consists of 8*8 array of DNP-II(equivalently 2*2 neural chips). Each processor board acn be built including linear array, 2-D mesh and 2-D torus. This flexibility supports efficiency of mapping from neural network models into parallel strucgure. The neural system accomplishes the performance of maximum 40 GCPS(giga connection per second) with 16 processor boards.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.263-266
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• 2003

In this paper, we have proposed a realization method of tactile sense of virtual objects using multi-layer Neural Networks(NN). Inputs of the NN are position data of non-rigid objects and outputs of the NN are forces at that time and point. First, the position and forte data are measured from non-rigid objects (a sponge and a balloon) using two PHANToMS, one as a master and the other as a slave manipulator, then the data are used to train a multi-layer Neural Networks whose inputs and outputs are designed to represent tactile information. The trained Neural Networks is used to regenerate the tactile sense on the virtual objects graphically made by a computer, and one can feel a quite similar sense of touch by using the system while touching the virtual objects.

• Annual Conference of KIPS
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• 2011.11a
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• pp.15-17
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• 2011

DVS 카메라는 인간의 눈을 모델링하여 만들어져서 화면의 변화에 반응하여 Address - Event - Representation 데이터를 생성하고 이 데이터는 jAER Viwer를 통해 확인할 수 있다. 이렇게 생성된 DVS 카메라의 데이터를 Spiking Neural Network의 입력으로 주기 위해 GPU를 이용한 Spiking Neural Network 시뮬레이터인 GPUSNN과 jAER 사이에 인터페이스가 필요하다. 이 인터페이스를 이용하면 GPUSNN을 통해 비전 알고리즘을 빠르고 효과적으로 Spiking Neural Network 시뮬레이션을 할 수 있을 것이다.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1293-1302
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• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.753-759
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• 2006

햅틱인터페이스 기술을 이용하면 가상물체의 형태를 만져보고 느껴볼 수 있다. 물체마다 다른 수학적 마찰력 모델을 적용하여 실감있는 마찰력 표현도 가능하다. 그러나 각 물체에 해당하는 마찰력 모델을 선정하는 것과 적절한 마찰계수 등을 반복적 실험을 통하여 알아내는 것은 쉽지 않다. 실제 물체의 마찰력이 알려진 마찰력 모델과 다르다면 수학적 모델로 표현할 수 없는 경우도 있다. 본 논문에서는 신경회로망 학습을 이용하여 마찰력 모델의 선택이나 마찰계수 등을 정하는 과정 없이 실제 물체의 마찰력을 표현하는 방법을 제시하고 있다. 상용 햅틱인터페이스 장치인 PHANToM 2 대를 이용하여 마찰력 획득 시스템을 구성하고 고무판, 종이 등의 물체 표면에서의 속도와 물체에 작용하는 힘을 획득하여 가공한 데이터를 입력 및 출력으로 갖는 신경회로망을 통해 학습시킨 후 OpenGL로 구현한 가상물체에 적용하여 보았다. Force/Torque 센서를 사용하지 못한 일부 문제가 있었으나 예상보다 사실적인 마찰력을 표현할 수 있었다.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.222-227
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• 2007

본 논문에서는 지체장애인들이 유효한 말초신경신호를 이용하여 컴퓨터를 사용할 수 있는 인터페이스를 개발하였다. 손목의 움직임을 통해 아래팔 4부분으로부터 근전도 (electromyogram, EMG) 신호를 추출하였고, 다층 인식 신경망을 사용하여 사용자의 의도를 추출하였다. 이를 통하여 마우스 커서의 움직임을 제어하고, 마우스 버튼을 클릭하는 동작을 할 수 있으며, 시각 디스플레이 장치에 표시된 핸드폰 자판과 같은 유저 인터페이스를 통해 컴퓨터에 글자를 입력할 수 있게 하였다. 추가적으로 Fitts' law를 사용하여 본 인터페이스의 사용성을 평가하였고, 이를 기존연구와 비교함으로써 본 인터페이스의 효용성을 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.42.3-42
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• 2002

Fuzzy Neural Network (FNN) is a compulsory element in a voice-controlled machine due to its inherent capability of interpreting imprecise natural language commands. To control such a machine, user's perception of imprecise words is very important because the words' meaning is highly subjective. This paper presents a voice based controller centered on an adaptable FNN to capture the user's perception of imprecise words. Conversational interface of the machine facilitates the learning through interaction. The system consists of a dialog manager (DM), the conversational interface, a Knowledge base, which absorbs user's perception and acts as a replica of human understanding of imprecise words,...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.223-227
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• 2003

A new flexible electronic packaging technology and its medical applications are presented. Conventional silicon chips and electronic modules can be considered as "mechanically rigid box." which does not bend due to external forces. This mechanically rigid characteristic prohibits its applications to wearable systems or bio-implantable devices. Using current MEMS (Microelectromechanical Systems) technology. a surface micromachined flexible polysilicon sensor array and flexible electrode array fer neural interface were fabricated. A chemical thinning technique has been developed to realize flexible silicon chip. To combine these techniques will result in a realization of truly flexible sensing modules. which are suitable for many medical applications.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.11-11
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• 2003