• Title/Summary/Keyword: Multi-Signal

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The Implementation of The Multi-Subject, Multi-Channel Optical Telemetry System for Physiological Signals

  • 박차훈;박종대;서희돈
    • 센서학회지
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    • 제9권6호
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    • pp.448-454
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    • 2000
  • This paper describes the implementation of a multi-subject, multi-channel optical telemetry system for the short range measurement of electrocardiograms (EKGs) a system which receives command signals and transmits physiological signals to the external system using LED (Light Emitting Diode) and PD (Photodiode). This system decreases the dependency of power supply voltage to the CMOS IC chips and a new enforced synchronization technique using infrared bi-directional communication has also been proposed. The telemetry IC with the size of $5.1{\times}5.1mm^2$ has the following functions: receiving of command signal, initialization of internal state of all functional blocks, decoding of subject selection signal, time division multiplexing of 4-channel modulated physiological signals, transmission of modulated signals to external system, and auto power down control.

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다중 반송파 CDMA 네트워크에서 부분 대역 간섭의 영향 (Effect of Partial-Band Interference in Multi-Carrier CDMA Network)

  • 노재성
    • 디지털콘텐츠학회 논문지
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    • 제5권3호
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    • pp.187-191
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    • 2004
  • 모바일 통신 채널의 빠른 변화는 다중 반송파 변조의 성능에 많은 영향을 준다. 본 논문에서는 다중 반송파 CDMA 네트워크의 BER 성능을 분석하였고 등가 신호 대 전체 잡음 전력비를 라이시안 페이딩, 부분대역간섭 다중접속 사용자 간섭채널에서 유도하였다. MC-CDMA 시스템의 역방향 링크 등가 SNIR을 사용하여 MC-CDMA/BPSK 신호의 성능을 부분대역간섭의 점유율과 간섭 전력에 따라서 평가하였다. 그리고 다중반송파 멀티미디어 시스템의 QoS를 향상하기 위한 부분대역간섭의 영향을 종합적으로 연구하였다.

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Multi-Textures를 이용한 Volume Rendering (Volume Rendering Using Multi-Textures)

  • 박재영;이병일;최흥국
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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    • pp.169-172
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    • 2000
  • 직접 volume rendering 방식에서 좋은 해상도의 이미지를 얻기 위해서 계산되는 많은 trilinear interpolation은 고성능 그래픽 워크스테이션이나 특별한 목적의 하드웨어 사양을 요구하며 제한적으로 구현이 되고 있다. 따라서 본 논문에서는 PC 그래픽 하드웨어 상에서 2D-Texture를 이용하여 volume rendering을 MRI head set 영상을 적용하여 구현해 보았다. 또한 최근에 지원되는 PC 그래픽 보드의 multi-texturing성능을 이용하여 volume rendering 할 수 있는 방법을 보여준다. 이러한 OuenGL 확장 기능을 이용하여 픽셀 연산과 rendering 성능을 PC 기반에서 항상 시켜 보았다.

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영상 신호에서 패턴인식을 이용한 다중 포인트 변위측정 (Displacement Measurement of Multi-point Using a Pattern Recognition from Video Signal)

  • 전형섭;최영철;박종원
    • 한국소음진동공학회논문집
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    • 제18권12호
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    • pp.1256-1261
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    • 2008
  • This paper proposes a way to measure the displacement of a multi-point by using a pattern recognition from video signal. Generally in measuring displacement, gab sensor, which is a displacement sensor, is used. However, it is difficult to measure displacement by using a common sensor in places where it is unsuitable to attach a sensor, such as high-temperature areas or radioactive places. In this kind of places, non-contact methods should be used to measure displacement and in this study, images of CCD camera were used. When multi-point is measure by using a pattern recognition, it is possible to measure displacement with a non-contact method. It is simple to install and multi-point displacement measuring device so that it is advantageous to solve problems of spatial constraints.

A Study of Multi-Target Localization Based on Deep Neural Network for Wi-Fi Indoor Positioning

  • Yoo, Jaehyun
    • 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.

다중 통합항법 시스템을 위한 랩뷰 기반의 사용자 인터페이스 설계 (LabVIEW-based User Interface Design for Multi-Integrated Navigation Systems)

  • 손재훈;정준우;오상헌;박준민;황동환
    • Journal of Positioning, Navigation, and Timing
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    • 제13권1호
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    • pp.75-83
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    • 2024
  • In order to reduce the time and cost of developing a navigation system, a performance evaluation platform can be used. A User Interface (UI) is required to effectively evaluate the performance, which sets parameters and gives navigation sensor signals and data display, and also displays navigation results. In this paper, a LabVIEW-based UI design method for multi-integrated navigation systems is proposed and implementation results are presented. The UI consists of a signal and data generation part and a signal and data processing part. The signal and data generation part sets parameters for the signal and data generation and displays the navigation sensor signal and data generation results. The signal and data processing part sets parameters for the signal and data processing and displays the navigation results. The signal and data generation part and signal and data processing part are designed to satisfy the requirements of the UI for a performance evaluation of the navigation system. In order to show the usefulness of the proposed UI design method, parameters of the signal and data generation and the signal and data processing are set through the LabVIEW-based UI, and the Global Positioning System (GPS) signal and inertial measurement unit data generation results and the navigation results of a GPS Software Defined Receiver (SDR) and inertial navigation system are confirmed. The implementation results show that the proposed UI design method helps users conduct an effective performance evaluation of navigation systems.

Estimating the Position of Mobiles by Multi-Criteria Decision Making

  • Lee, Jong-Chan;Ryu, Byung-Han;Ahn, Jee-Hwan
    • ETRI Journal
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    • 제24권4호
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    • pp.323-327
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    • 2002
  • In this study, we propose a novel mobile tracking method based on Multi-Criteria Decision Making (MCDM), in which uncertain parameters-the received signal strength, the distance between the mobile and the base station, the moving direction, and the previous location-are used in the decision process using the aggregation function in the fuzzy set theory. Through numerical results, we show that our proposed mobile tracking method provides a better performance than the conventional method using the received signal strength.

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다층 배선에서 차폐효과 모델 및 스위칭에 미치는 영향 (Shielding effect model and Signal Switching in the multi-layer interconnects)

  • 진우진;어영선
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 추계종합학술대회 논문집
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    • pp.1145-1148
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    • 1998
  • New capacitance modeling and transient analysis for multi-layer interconnects with shielding effect are presented. The upper layer capacitances with under-layer shielding lines are represented by introducing a filling factor η which can be defined as the ratio of upper-layer line length to the total under-layer line width. The upper-layer effective self capacitances considering two extreme cases which the underlayer metals are assumed as a ground or as a Vdd are modeled. The signal transient analysis with shielding effect model is performed.

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FUNDAMENTAL STUDY OF INTELLIGENT MUSTI-FUNCTIONAL INSTRUMENTATION AND ITS SIGNAL PRICESSING ABILITIES

  • Wakuya, Hiroshi;Shimoyama, Akihiko;Shida, Katsunori
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.166-169
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    • 1995
  • An intelligent system which is an integration of multi-functional instrumentation (MFI) and a neural network is discussed. According to some experiments of temperature and wind velocity it is clear that this system can learn the data structure of two parameters above. So it makes good performances for estimations of non-sample data.

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