• 방송공학회논문지
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• 제19권6호
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• pp.967-970
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• 2014

이 논문에서는 M-FSK(frequency shift keying) 변조신호를 자동으로 분류하는데 필요한 효율적인 첨두 검출 방법을 제안하였다. 다른 디지털 변조신호와 FSK 신호는 진폭 스펙트럼의 특성을 이용하여 분류할 수 있다. FSK 신호의 진폭 스펙트럼은 다른 디지털 변조신호와 다르게 변조차수와 동일한 수의 첨두를 나타낸다. 일반적으로 신호의 첨두를 검출하기 위해서는 임계치가 필요한데, 변조인식과 같이 사전에 신호에 대한 정보가 없는 경우 임계치를 정하기 어려운 점이 있다. 이 논문에서는 진폭 스펙트럼의 히스토그램을 이용하여 자동으로 간단하게 임계치를 결정하는 방법을 제시하였다. 모의실험 결과 적은 수의 표본과 잡음이 많은 환경에서도 매우 우수한 분류확률을 나타내었다.

• 한국컴퓨터정보학회논문지
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• 제13권7호
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• pp.67-73
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• 2008

본 논문에서는 무선 센서 노드의 실내 위치 추적 시스템을 제안한다. 위치 추정에 사용하는 센서 값으로 RF 인터페이스의 수신 신호 강도 (RSSI)를 사용한다. 이동 노드를 부착한 사용자와 실내에 고정된 다수의 고정 노드의 신호 강도를 수신하여 사용자의 위치를 결정한다. 제안한 시스템은 측정에 의한 2.4GHz log-normal path loss 모델의 수신강도와 유클리드 거리 계산 방법과 신호 강도를 결합한다. 실험결과를 통해서 1.3m 이내의 오차로 위치를 추정함을 확인하였다.

• 전자공학회논문지B
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• 제32B권10호
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• pp.1280-1285
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• 1995

In this paper the optimized overlap driving scheme for improving the reduction problem of the operating voltage range occured by the overlap driving scheme proposed precedently and increasing the contrast ratio of screen image in the simple matrix LCDs is proposed. The characteristic estimation of the proposed method was performed in a condition that the number of scan electrodes was 120 and the threshold voltage of LC pixel was 2V and the overlap rate of scan signal was varied from 0% to 40% . As a result of estimation compared with the overlap driving scheme proposed precedently, this new method was certified as a method which it could increase the operating voltage range of the LC pixel by 16% in 20% overlap condition and it's operating voltage range was also increased very much with the increase of the overlap rate. Consequently this newly proposed method was certified as a method which it could maintain the improvement effect of the operating characteristics obtained by the overlap driving scheme proposed precedently with the big improvement in the contrast ratio of screen image.

• 한국컴퓨터산업학회논문지
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• 제5권9호
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• pp.987-992
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• 2004

비디오 시퀀스의 현재 블록의 움직임 벡터와 이전 블록의 움직임 벡터는 시간적 상관성을 갖고있다. 본 논문에서는 현재 프레임 블록의 인접 블록으로부터 예측된 움직임 정보를 구하여, 이를탐색 원점으로 하여 수정된 다이아몬드 지역 레이더 패턴으로 블록 정합을 수행하는 블록 정합움직임 추정 방식을 제안한다. 실험 결과 제안된 방식은 전역탐색을 제외한 기존의 방식들에 비해 PSNR 값에 있어서 평균적으로 0.02~0.37[dB] 개선되고 움직임 벡터 예측의 속도에 있어서 약 14~24% 이상의 높은 성능 향상을 보였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권1호
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• pp.55-64
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• 2004

Conventional bipolar surface electromyography(EMG) technique detects only the superimposed electromyographic activity of a large number of motor units due to its low spatial resolution. For the diagnosis of neuromuscular disorder, the information of single MU is required. In this paper, 9 channel array surface electrode system was as designed and MLoG filter was proposed. Also the MCPT(modified convolution processing technique)method was proposed for the improvement of MUAP resolution. For performance evaluation, power spectrum analysis of random data and raw EMG signal comparison of MUAP shape and quantitative estimation of SNR were executed. As a result, the MUAP resolution improvement of 32％ was obtained from the standpoint of the signal-to-noise ratio(SNR).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.2077-2078
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• 2011

Now a days, the induction motor is widely used in industry automation. Without monitoring the motor fault, maintenance cost is increased undesirably high. The slip frequency is included in the feature frequency, so rotating rotor speed is needed. In this paper, a sensorless motor speed estimation method, rotor slot harmonic(RSH) method is suggested and a solution of rotor bar diagnosis is proposed for motor running with light-load. When the rotor is rotating, it shows the harmonic signal of back-emf voltage related with number of rotor slot. So from the power spectrum of current signal, we can find the rotor speed.

• Journal of information and communication convergence engineering
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• 제10권4호
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• pp.349-358
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• 2012

Over a wireless sensor network (WSN), accurate localization of sensor nodes is an important factor in enhancing the association between location information and sensory data. There are many research works on the development of a localization algorithm over three-dimensional (3D) space. Recently, the complexity-reduced 3D trilateration localization approach (COLA), simplifying the 3D computational overhead to 2D trilateration, was proposed. The method provides proper accuracy of location, but it has a high computational cost. Considering practical applications over resource constrained devices, it is necessary to strike a balance between accuracy and computational cost. In this paper, we present a novel 3D localization method based on the received signal strength indicator (RSSI) values of four anchor nodes, which are deployed in the initial setup process. This method provides accurate location estimation results with a reduced computational cost and a smaller number of anchor nodes.

• 한국통신학회논문지
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• 제19권2호
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• pp.345-353
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• 1994

본 논문에서는 Sample Array Covariance Matrix의 대각선요소들의 평균치를 취하여 이를 대각선 요소값들로 대치하여 도래방향각 예측을 수행하는 소위 'Averaged MUSIC' 방법이 낮은 신호대잡음비, 신호원들이 근접해 있는 경우, Sensor의 수가 제한되어 있는 경우등에서 MUSIC에 비하여 훨씬 고해상도의 DOA 예측을 수행함을 보였다. 이를 위해서 통계적인 방법을 사용하여서 한 두가지 경우에 나오는 특별한 결과를 배제하고 가능한한 정확한 결과 비교를 위해 노력하였다.

• Journal of Positioning, Navigation, and Timing
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• 제10권1호
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.95-100
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• 2024

Cyclic Delay Diversity (CDD) is a diversity scheme used in OFDM-based telecommunication systems, transforming spatial diversity into frequency diversity and thus avoiding intersymbol interference without entailing the receiver to be aware of the transmission strategy making the signal more reliable achieving full diversity gain in cooperative systems. Here the analyzation of the influence of CDD-SC scheme in Cognitive Radio Network (CRN) is done with the challenge of overcoming the complication called channel estimation along with overhead in CNR. More specifically, the closed-form expressions for outage probability and symbol error rate are divided under different frequencies among independent and identically distributed (i.i.d.) frequency selective fading channel model i.e., the signal is divided into different frequencies and transmitted among several narrow band channels of different characteristics. It is useful in the reduction of interference and crosstalk. The results reveal the diversity order of the proposed system to be mainly affected by the number of multipath components that are available in the CNR.