• 한국컴퓨터정보학회논문지
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• 제13권5호
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• pp.111-116
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• 2008

레이더 시스템은 간섭채널에서 목표물을 신속, 정확하게 예측하여야 한다. 무선채널의 간섭요소로는 인공구조물, 자연구조물에 의해서 다중경로가 형성되어 신호의 추정이 어렵다. 이러한 간섭신호를 제거하기 위해서 디지털 빔형성, 적응배열안테나 등 많은 연구가지속 되어왔다. 본 논문에서는 적응배열 안테나와 코히어런트 간섭신호를 제거하는 SPT-SALCMV 빔형성 알고리즘을 제안하였다. 적응 배열은 간섭신호의 방향에 대해서는 널 패턴을 형성하여 이득을 감소시킨다. 그리고 표적신호 방향으로는 빔 패턴의 이득을 일정하게 유지함으로서 원하는 신호를 추정한다. 본 논문에서 제안한 SPT-SALCMV 알고리즘은 목표물에 대한 위치를 정확히 수신하였다. 그러나 기존의 SPT-LCMV 알고리즘은 약 30 정도의 빔 오차가 생겼다. 따라서 본 논문에서 제안한 SPT-SALCMV 알고리즘이 기존의 SPT-LCMV알고리즘보다 우수함을 입증하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.775-778
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• 2016

본 논문에서는 전자전 신호 환경에서 ES(Electronic Support) 시스템의 레이더 신호의 PRI 변조 형태를 자동으로 인식하는 새로운 방법을 제안한다. 제안방법은 레이더 펄스 신호의 펄스반복간격인 PRI(Pulse Repetition Interval)값의 패턴을 저장하고 통계적 테이터를 사용하여 먼저 2개의 클래스로 분류한다. 분류된 2개의 클래스를 PRI의 통계적 특성을 이용하여 각각의 PRI 신호를 인식한다. 제안 방법을 고정(constant)PRI, 지터(jitter)PRI, 스태거(stagger)PRI, D&S(dwell&switch)PRI, 슬라이딩(sliding) PRI 등 5종류의 다양한 PRI 신호들에 적용한 결과 정확히 PRI 변조방식을 식별하였다.

• 한국군사과학기술학회지
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• 제20권3호
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• pp.328-336
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• 2017

The goal of this study is simulation of optimal search pattern of ships based on performance surface which are reflected underwater environmental. The process is as follows. First, temporal and spatial environmental database are extracted in complex environment and input hull mounted SONAR system parameters. The environmental database and SONAR system parameters are substituted to SONAR equations, and calculate signal excess, detection probability, detection range. And then, the performance surface, which can be used to provide operational insight of SONAR detection performance, are pictorialized. Finally, optimal search pattern of ships are simulated using genetic algorithm based on performance surface. And then, we certify optimal search pattern in various ways.

• 한국전자통신학회논문지
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• 제9권10호
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• pp.1197-1205
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• 2014

최근 초고화질(4K-UHD) 영상 시스템의 신호전송은 비압축 고속 데이터로 전송되며 고속 신호의 인터페이스 구간에 서로 다른 케이블 사이에서 나타나는 EMI, 스큐(skew) 문제로 인하여 영상신호의 왜곡, 지터 등으로 시스템 구현에 한계가 있다. 이와 같이 비압축 고속 데이터를 고속전송하기 위하여 V-by-One HS 인터페이스 기법을 적용하여 본 논문에서는 고속 영상신호에 대하여 HSD(High Speed Differential) 전송선로의 신호무결성을 분석하였다. UHD 영상패턴 제어 인터페이스의 PCB 설계 방법을 RF 전송기법으로 적용하였으며 구현된 4K-UHD급 영상패턴 제어 신호발생기의 V-by-One HS 영상신호를 측정한 결과, 전송품질이 고속전송신호규격에 만족함을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2513-2533
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• 2018

In cognitive radio technology, the overall efficiency of communications systems can be improved without allocating additional bands by allowing a secondary system to utilize the licensed band when the primary system, which has the right to use the band, does not use it. In this paper, we propose a fast and reliable common channel initialization protocol without any exchange of initialization messages between the cluster head and the member nodes in cognitive ad-hoc networks. In the proposed method, the cluster and member nodes perform channel-based spectrum sensing. After sensing, the cluster head transmits a system activation signal through its available channels with a predetermined angle difference pattern. To detect the cluster head's transmission channels and to join the cluster, each member node implements fast Fourier transform (FFT) and computes autocorrelation for the angle difference sequence of the received signal patterns. This is compared to the predetermined reference angle difference pattern. The join-request and channel-decision procedures are presented in this paper. Performance evaluation of the proposed method is presented in the simulation results.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.398-401
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• 1997

The EMG signal of spinal cord injured patient is very feeble because that the information from central nervous system is not sufficiently transmitted to molter neuron or muscle fiber. Therefore the observer can not observe contraction and relaxation movement of muscle from the raw EMG signal. In this paper, we propose the muscle contraction and relaxation pattern analysis method of spinal cord injured patient whose EMG signal is composed of the sum of motor unit action potential train with additive white Gaussian noise and impulsive noise. From the EMG model, we denoise impulsive noise using median filter which is a kind of nonlinear filter and the output of median filter is transformed to wavelet transform domain for denoising additive white Gaussian noise using threshold level removal technique. As a result, we can obtain the clear contraction and relaxation pattern.

• International Journal of Internet, Broadcasting and Communication
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• 제7권2호
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.

• 한국안전학회지
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• 제37권2호
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• pp.69-75
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• 2022

Fire-alarm systems are safety equipment that facilitate rapid evacuation and early suppression in case of fire. It is highly desirable that fire-alarm systems have low false-alarm rates and are thus reliable. Until now, researchers have attempted to improve detector performance by applying new technologies such as IoT. To this end, IoT-based fire-detection systems have been developed. However, due to scarcity of large-scale operational data, researchers have barely studied malfunctioning in fire-alarm systems or attempted to reduce false-alarm rates in these systems. In this study, we analyzed false-alarm rates of smoke/temperature detectors and unwanted fire-alarm signal patterns at K institution, where Korea's largest IoT-based fire-detection system operates. After analyzing the fire alarm occurrences at the institution for five years, we inferred that the IoT-based fire-detection system showed lower false-alarm rates compared to the automatic fire-detection equipment. We analyzed the detection pattern by dividing it into two parts: normal operation and unwanted fire alarms. When a specific signal pattern was filtered out, the false-alarm rate was reduced to 66.9% in the smoke detector and to 46.9% in the temperature detector.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.769-771
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• 2000

In this paper, pattern recognition scheme for EMG signal using artificial neural network is proposed. For manipulating ability, the movements of human arm are classified into several categories EMG signals of appropriate muscles are collected during arm movement. Patterns of EMG signals of each movement are recognized as follows: 1) The features of each EMG signal are extracted. 2) With these features, the neural network is trained by using feedforward error back-propagation (FFEBP) algorithm. The results show that the arm movements can be classified with EMG signals at high accuracy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.150-154
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.