• E2M - 전기 전자와 첨단 소재
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• 제9권8호
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• pp.825-830
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• 1996

In this study, Characteristics of Ultrasonic Transducer fabricated with porous piezoelectric resonator, 3-D underwater object restoration using the self made ultrasonic transducer and modified SCL(Simple Competitive Learning) neural network are investigated. The self-made transducer was satisfied the required condition of ultrasonic transducer in water, and the modified SCL neural network using the acquired object data 16*16 low resolution image was used for object restoration of $32{\times}32$ high resolution image. The experimental results have shown that the ultrasonic transducer fabricated with porous piezoelectric resonator could be applied for SONAR system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.939-941
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• 1999

Recognition rates of 3-D underwater object using the SCL neural network and the SOFM neural network were 91.8% and 95.9%, respectively.

• E2M - 전기 전자와 첨단 소재
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• 제10권9호
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• pp.916-921
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• 1997

In this study Characteristics of 3-D underwater object recognition independent of translation using the self-made ultrasonic sensor fabricated with porous piezoelectric resonator and presented. The sensor was satisfied with requirement of ultrasonic sensor. The recognition rates for the training data and the testing data are 97.45 and 91.25[%] respectively using the self-made ultrasonic sensor and SCL(Simple Competitive Learning) neural network. According to the experimental results It is believed that the self-made ultrasonic sensor can be applied as sensor of SONAR system.

• 센서학회지
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• 제29권1호
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• pp.68-73
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• 2020

This paper proposes an asynchronous circuit design methodology using a new Single Gate Sleep Convention Logic (SG-SCL) with advantages such as low area overhead, low power consumption compared with the conventional null convention logic (NCL) methodologies. The delay-insensitive NCL asynchronous circuits consist of dual-rail structures using {DATA0, DATA1, NULL} encoding which carry a significant area overhead by comparison with single-rail structures. The area overhead can lead to high power consumption. In this paper, the proposed single gate SCL deploys a power gating structure for a new {DATA, SLEEP} encoding to achieve low area overhead and low power consumption maintaining high performance during DATA cycle. In this paper, the proposed methodology has been evaluated by a liquid state machine (LSM) for pattern and digit recognition using FPGA and a 0.18 ㎛ CMOS technology with a supply voltage of 1.8 V. the LSM is a neural network (NN) algorithm similar to a spiking neural network (SNN). The experimental results show that the proposed SG-SCL LSM reduced power consumption by 10% compared to the conventional LSM.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.326-328
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• 1994

A modified Kohonen's simple Competitive Learning(SCL) algorithm which has binary reinforcement function and a constant adaptation gain is proposed. In contrast to the time-varing adaptation gain of the original Kohonen's SCL algorithm, the proposed algorithm uses a constant adaptation gain, and adds a binary reinforcement function in order to compensate for the lowered learning ability of SCL due to the constant adaptation gain. Since the proposed algorithm does not have the complicated multiplication, it's digital hardware implementation is much easier than one of the original SCL.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제48권6호
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• pp.456-461
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• 1999

In this study, the characteristics of Ultrasonic Transducer fabricated with PZT-Polymer 1-3 type piezoelectric ceramic/polymer composite are investigated. 3-D underwater object restoration using the self-made ultrasonic transducer and modified SCL(Simple Competitive Learning) neural network was presented. The ultrasonic transducer was satisfied with the required condition of commerical ultrasonic transducer in underwater. The modified SCL neural network using the acquired object data $16\times16$ low resolution image was used for object restoration of $32\times32$ high resolution image. The experimental results have shown that the ultrasonic transducer fabricated with PZT-Polymer 1-3 type piezoelectric ceramic/polymer composite could be applied for SONAR system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.349-352
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• 1994

An object recognition and restoration using ultrasound sensors and neural networks are presented. The planar arrangement of the sensor is used to reduce the interference effects between sensors. The SOFM(Self-Organizing Feature Map) Neural Network and SCL(Simple Competitive Learning) method are learned with the acquired data. Lab experiments were performed that the object can be recognized ed the resolutions of the object can be enhanced by using the small number of the ultrasound array and neural networks.

• 감성과학
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• 제21권1호
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• pp.177-186
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• 2018

감성은 복잡하고 다양한 요인들에 의해 영향을 받기 때문에 다각적인 측면에서 고려되어야 한다. 본 연구에서는 심리 평가 척도의 하나인 각성(arousal) 지표와 다중 생체신호에서 추출된 생체지표 반응을 이용하여 중립 및 부정 감성(슬픔, 공포, 놀람)의 분류하였다. 이를 위하여 감성에 따른 생체지표 반응의 차이를 확인하였고, 다중 신경망 알고리즘 기반의 감성 인식기를 적용하여 이들 감성이 얼마나 정확하게 분류되는가를 확인하였다. 총 146명의 실험 참가자(평균 연령 $20.1{\pm}4.0$, 남성 41%)를 대상으로 감성 유발 자극을 제시하고 동시에 생체신호(심전도, 혈류맥파, 피부전기활동)를 측정하였다. 또한 감성 유발 자극에 대한 심리 반응을 감성 평가 척도로 평가하였다. 측정된 생체신호에서 심박률(HR), NN 간격의 표준편차(SDNN), 혈류량(BVP), 맥파전달시간(PTT), 피부전도수준(SCL), 피부전도반응(SCR)을 추출하였다. 결과 분석을 위하여 감성 자극에 대한 각성도와 안정 상태와 감성 상태의 생체지표 반응을 활용하였다. 또한 감성 분류를 위하여 다중 신경망 기반의 감성 인식기를 활용하였다. 그 결과, 감성에 따른 생체지표 반응의 차이를 확인하였고, 이들 감성의 분류 성능은 각성도와 모든 생체지표 특징들을 조합하였을 때 정확도가 가장 높음(86.9%)을 확인하였다. 본 연구는 심리 및 생체지표 추출과 기계학습 기술의 적용을 통하여 부정 감성을 분류할 수 있음을 제안하며, 이는 인간의 감성을 탐지하는 감성 인식 기술을 확립하는데 기여할 것으로 예상한다.