• Title/Summary/Keyword: 검출확률

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A Cooperative K-out-of-n Spectrum Sensing Method Considering Optimal Threshold (최적의 임계값을 고려한 K-out-of-n 협력 스펙트럼 검출 기법)

  • Choi, Moon-Geun;Kong, Hyung-Yun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.8
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    • pp.761-767
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    • 2011
  • In this paper, to improve performance of spectrum sensing, we propose the method which can find optimal threshold based on power of PU(Primary User) signal. To find optimal threshold value, we will use mathematical method, and find threshold which can has lowest error probability. Each SU(Secondary User) use this threshold and All Su makes local decision. All Su Send local decision to FC(Fusion Center). In this paper we consider K-out-of-n rule to combining local decision. To make global decision value, FC find optimal n. In the FC. FC received local decision which has lowest error probability and using optimal n and these vaule. FC make global decision value. In this paper, to analysis performance proposed scheme, we simulate proposed scheme using matlab and compare with traditional OR Rule. As a result of simulation, we can know that preposed scheme can get a better performance than traditional OR rule.

Voice Activity Detection Using Global Speech Absence Probability Based on Teager Energy in Noisy Environments (잡음환경에서 Teager Energy 기반의 전역 음성부재확률을 이용하는 음성검출)

  • Park, Yun-Sik;Lee, Sang-Min
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.1
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    • pp.97-103
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    • 2012
  • In this paper, we propose a novel voice activity detection (VAD) algorithm to effectively distinguish speech from nonspeech in various noisy environments. Global speech absence probability (GSAP) derived from likelihood ratio (LR) based on the statistical model is widely used as the feature parameter for VAD. However, the feature parameter based on conventional GSAP is not sufficient to distinguish speech from noise at low SNRs (signal-to-noise ratios). The presented VAD algorithm utilizes GSAP based on Teager energy (TE) as the feature parameter to provide the improved performance of decision for speech segments in noisy environment. Performances of the proposed VAD algorithm are evaluated by objective test under various environments and better results compared with the conventional methods are obtained.

Impulse Noise Removal Using Noise Detector and Total Variation Optimization (잡음 검출기와 총변량 최적화를 이용한 영상의 임펄스 잡음제거)

  • Lee Im-Geun
    • The Journal of the Korea Contents Association
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    • v.6 no.4
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    • pp.11-18
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    • 2006
  • A new algorithm for removing salt and pepper impulse noise in image using impulse noise detector and total variation optimization is presented. The proposed two types of noise detectors which are based on the adaptive median filter, can detect impulse noise with high accuracy while reducing the probability of detecting image details as impulses. And the detectors maintain its performance independent of noise density. For removing impulses, total variation optimization is applied only to those detected noise candidate to reduces unnecessary computation. The proposed approach successfully remove impulse noise while preserving image details.

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Voice Activity Detection based on DBN using the Likelihood Ratio (우도비를 이용한 DBN 기반의 음성 검출기)

  • Kim, S.K.;Lee, S.M.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.8 no.3
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    • pp.145-150
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    • 2014
  • In this paper, we propose a novel scheme to improve the performance of a voice activity detection(VAD) which is based on the deep belief networks(DBN) with the likelihood ratio(LR). The proposed algorithm applies the DBN learning method which is trained in order to minimize the probability of detection error instead of the conventional decision rule using geometric mean. Experimental results show that the proposed algorithm yields better results compared to the conventional VAD algorithm in various noise environments.

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Layered Object Detection using Gaussian Mixture Learning for Complex Environment (혼잡한 환경에서 가우시안 혼합 모델을 이용한 계층적 객체 검출)

  • Lee, Jin-Hyeong;Kim, Heon-Gi;Jo, Seong-Won;Kim, Jae-Min
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.435-438
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    • 2007
  • 움직이는 객체를 검출하기 위해서 정확한 배경을 사용하기 위해 널리 사용되는 방법으로는 가우시안 혼합 모델이다. 가우시안 혼합 모텔은 확률적 학습 방법을 사용하는데, 이 방법은 움직이는 배경일 경우와 이동하던 물체가 정지하는 경우 배경을 정확히 모델링하지 못한다. 본 논문에서는 확률적 모델링을 통해 혼잡한 배경을 모델링하고 객체의 계층적 처리를 통해 보다 정확한 배경으로 갱신할 수 있는 학습 방법을 제안한다.

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Study on the size of experiments in mixed models (혼합모형에서 실험의 크기에 관한 연구)

  • 이연수;임용빈;김재주
    • The Korean Journal of Applied Statistics
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    • v.12 no.2
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    • pp.593-603
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    • 1999
  • 표본의 크기의 제1종오류의 확률 $\alpha$, 실용적으로 차이가 있다고 판독되어서 검출하고자하는 요인효과의 오차에 대한 상대적인 크기, 그 값에서의 제2종오류의 확률 $\beta$에 따라서 결정된다. 이 논문에서, 우리는 고정요인과 랜덤요인이 포함된 실험계획에서 표본의 크기를 결정하는 방법을 간단한 MATLAB 프로그램을 사용하여 고려한다. 분할법과 지분요인배치법의 예제를 들어 유의수준 $\alpha$와 최소 표준과 검출효과 $\Delta^*$에서 검정력이 적어도 $1-\beta$를 갖도록 표본의 크기를 결정한다

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Performance Analysis of Multi-channel Joint Detection for CDMA in Multi-path Fading Channel (다중경로 페이딩 채널에서의 CDMA 다중채널 결합 검출 방식의 성능 분석)

  • 황용선;이종훈;김동구
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.8A
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    • pp.1099-1106
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    • 1999
  • In this paper, the bit error ratio(BER) performance of multi-carrier CDMA system in multi-user/multi-path environment is analytically derived, and effect of interferences due to multi-user, multi-carrier, multi-path is analyzed. A multi-carrier/multi-user/multi-path joint detection scheme incorporating a decorrelating detector is proposed, and its performance as well as the enhancement of noise due to decorrelating process are analyzed. BER of the proposed joint detection scheme is only slightly degraded compared to the ideal case of single user environment.

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Design of Automation (RPA) for uploading workout videos to YouTube highlights through deep learning facial expression recognition (딥러닝 표정 인식을 통한 운동 영상 유튜브 하이라이트 업로드 자동화(RPA) 설계)

  • Shin, Dong-Wook;Moon, NamMee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.655-657
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    • 2022
  • 본 논문은 유튜브에 업로드 된 운동 영상을 시청하는 사람의 얼굴 영역을 YoloV3을 이용하여 얼굴 영상에서 눈 및 입술영역을 검출하는 방법을 연구하여, YoloV3은 딥 러닝을 이용한 물체 검출 방법으로 기존의 특징 기반 방법에 비해 성능이 우수한 것으로 알려져 있다. 본 논문에서는 영상을 다차원적으로 분리하고 클래스 확률(Class Probability)을 적용하여 하나의 회귀 문제로 접근한다. 영상의 1 frame을 입력 이미지로 CNN을 통해 텐서(Tensor)의 그리드로 나누고, 각 구간에 따라 객체인 경계 박스와 클래스 확률을 생성해 해당 구역의 눈과 입을 검출한다. 검출된 이미지 감성 분석을 통해, 운동 영상 중 하이라이트 부분을 자동으로 선별하는 시스템을 설계하였다.

A Study on The Hybrid Acquisition Performance of MC DS-CDMA Over Multipath Fading Channel (다중경로 환경에서 MC DS-CDMA시스템의 직.병렬 혼합 동기 획득에 관한 연구)

  • Kim, Won-Sbu;Kim, Kyung-Won;Park, Jin-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.10
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    • pp.1968-1976
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    • 2007
  • This paper proposes a hybrid pseudo-noise (PN) code acquisition scheme for Multicarrier Direct Sequence - Code Division Multiple Access (MC DS-CDMA) mobile communication systems on the code acquisition performance for Nakagami-m fading channel. The hybrid acquisition scheme combines parallel search with serial search to cover the whole uncertainty region of the input code phase. It has a much simpler acquisition hardware structure than the total parallel acquisition and can achieve the mean acquisition time (MAT) slightly inferior to that of the total parallel acquisition. The closed-form expressions of the detection and false-alarm probabilities are derived.

Detection Probability as a Symbol Synchronization Timing at the Lead of Each Received Delay OFDM Signal in Multipath Delay Profile (멀티패스 지연프로필의 각 수신지연파의 선두에서 OFDM 신호의 심벌 동기타이밍으로의 검출확률)

  • Joo, Chang-Bok;Park, Dong-Ho
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.44 no.2
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    • pp.55-61
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    • 2007
  • In this paper, we represent the maximum detection probability formulas of symbol synchronization timing at each received delay signal in multipath channel delay profile in the multiplied correlation and difference type correlated symbol synchronization timing detection method. The computer simulation results show that the correlation symbol timing detection method have maximum detection probability at the lead of received delay signal of highest amplitude, but the difference type of correlation symbol timing detection method always have maximum detection probability at the lead of first received delay signal in the multipath channel models. Using this results, we show the BER characteristics difference between the IEEE802.11a OFDM signals which is obtained in case of the symbol synchronization timing is taken at zero error(perfect) timing position and at -1 sample error symbol timing position from perfect timing position in the multipath channel models regardless the length of channel delay spread.