• Title/Summary/Keyword: Fusion Rule

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Analysis and Optimization of Cooperative Spectrum Sensing with Noisy Decision Transmission

  • Liu, Quan;Gao, Jun;Guo, Yunwei;Liu, Siyang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.4
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    • pp.649-664
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    • 2011
  • Cooperative spectrum sensing (CSS) with decision fusion is considered as a key technology for tackling the challenges caused by fading/shadowing effects and noise uncertainty in spectrum sensing in cognitive radio. However, most existing solutions assume an error-free decision transmission, which is obviously not the case in realistic scenarios. This paper extends the general decision-fusion-based CSS scheme by considering the fading/shadowing effects and noise corruption in the common control channels. With this more practical model, the fusion centre first estimates the local decisions using a binary minimum error probability detector, and then combines them to get the final result. Theoretical analysis and simulation of this CSS scheme are performed over typical channels, which suggest some performance deterioration compared with the pure case that assumes an error-free decision transmission. Furthermore, the fusion strategy optimization in the proposed cooperation model is also investigated using the Bayesian criteria. The numerical results show that the total error rate of noisy CSS is higher than that of the pure case, and the optimal values of fusion parameter in the counting rule under both cases decrease as the local detection threshold increases.

Finger Vein Recognition based on Matching Score-Level Fusion of Gabor Features

  • Lu, Yu;Yoon, Sook;Park, Dong Sun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.2
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    • pp.174-182
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    • 2013
  • Most methods for fusion-based finger vein recognition were to fuse different features or matching scores from more than one trait to improve performance. To overcome the shortcomings of "the curse of dimensionality" and additional running time in feature extraction, in this paper, we propose a finger vein recognition technology based on matching score-level fusion of a single trait. To enhance the quality of finger vein image, the contrast-limited adaptive histogram equalization (CLAHE) method is utilized and it improves the local contrast of normalized image after ROI detection. Gabor features are then extracted from eight channels based on a bank of Gabor filters. Instead of using the features for the recognition directly, we analyze the contributions of Gabor feature from each channel and apply a weighted matching score-level fusion rule to get the final matching score, which will be used for the last recognition. Experimental results demonstrate the CLAHE method is effective to enhance the finger vein image quality and the proposed matching score-level fusion shows better recognition performance.

Comparing Accuracy of Imputation Methods for Categorical Incomplete Data (범주형 자료의 결측치 추정방법 성능 비교)

  • 신형원;손소영
    • The Korean Journal of Applied Statistics
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    • v.15 no.1
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    • pp.33-43
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    • 2002
  • Various kinds of estimation methods have been developed for imputation of categorical missing data. They include category method, logistic regression, and association rule. In this study, we propose two fusions algorithms based on both neural network and voting scheme that combine the results of individual imputation methods. A Mont-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data pattern are (1) input-output function, (2) data size, (3) noise of input-output function (4) proportion of missing data, and (5) pattern of missing data. Experimental study results indicate the following: when the data size is small and missing data proportion is large, modal category method, association rule, and neural network based fusion have better performances than the other methods. However, when the data size is small and correlation between input and missing output is strong, logistic regression and neural network barred fusion algorithm appear better than the others. When data size is large with low missing data proportion, a large noise, and strong correlation between input and missing output, neural networks based fusion algorithm turns out to be the best choice.

Image Registration and Fusion between Passive Millimeter Wave Images and Visual Images (수동형 멀리미터파 영상과 가시 영상과의 정합 및 융합에 관한 연구)

  • Lee, Hyoung;Lee, Dong-Su;Yeom, Seok-Won;Son, Jung-Young;Guschin, Vladmir P.;Kim, Shin-Hwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.6C
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    • pp.349-354
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    • 2011
  • Passive millimeter wave imaging has the capability of detecting concealed objects under clothing. Also, passive millimeter imaging can obtain interpretable images under low visibility conditions like rain, fog, smoke, and dust. However, the image quality is often degraded due to low spatial resolution, low signal level, and low temperature resolution. This paper addresses image registration and fusion between passive millimeter images and visual images. The goal of this study is to combine and visualize two different types of information together: human subject's identity and concealed objects. The image registration process is composed of body boundary detection and an affine transform maximizing cross-correlation coefficients of two edge images. The image fusion process comprises three stages: discrete wavelet transform for image decomposition, a fusion rule for merging the coefficients, and the inverse transform for image synthesis. In the experiments, various types of metallic and non-metallic objects such as a knife, gel or liquid type beauty aids and a phone are detected by passive millimeter wave imaging. The registration and fusion process can visualize the meaningful information from two different types of sensors.

Role of the Promoter Region of a Chicken H3 Histone Gene in Its Cell Cycle Dependent Expression

  • Son, Seung-Yeol
    • BMB Reports
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    • v.32 no.4
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    • pp.345-349
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    • 1999
  • We fused the promoter region of an H3.2 chicken histone gene, whose expression is dependent on the cell cycle, to the 5' coding region of an H3.3 chicken histone gene, which is expressed constitutively at a low level throughout the cell cycle. This fusion gene showed a cell cycle-regulated pattern of expression, but in a different manner. The mRNA level of the fusion gene increase during the S phase of the cell cycle by about 3.7-fold at 6 h and 2.7-fold at 12 h after the serum stimulation. The mRNA level of the intact H3.2 gene, however, increased by an average of 3.6-fold at 6 h and 8.7-fold at 12 h. This different expression pattern might be due to the differences in their 3' end region that is responsible for mRNA stability. The 3' end of the H3.2 mRNA contains a stem-loop structure, instead of a poly(A) tail present in the H3.3 mRNA. We also constructed a similar fusion gene using a H3.3 histone gene whose introns had been eliminated to rule out the possibility of involvement of the introns in cell cycle-regulated expression. The expression of this fusion gene was almost identical to the fusion gene made previously. These results indicate that the promoter region of the H3.2 gene is only partially responsible for its expression during the S phase of the cell cycle.

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Implementation of a sensor fusion system for autonomous guided robot navigation in outdoor environments (실외 자율 로봇 주행을 위한 센서 퓨전 시스템 구현)

  • Lee, Seung-H.;Lee, Heon-C.;Lee, Beom-H.
    • Journal of Sensor Science and Technology
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    • v.19 no.3
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    • pp.246-257
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    • 2010
  • Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

An Information Fusion-based Disaster Information System Framework (정보융합기반 재난정보시스템 프레임워크에 관한 연구)

  • Park, Choong-shik
    • Journal of the Society of Disaster Information
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    • v.5 no.2
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    • pp.40-48
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    • 2009
  • DIS(Disaster Information System) is the information system supporting prevention, readiness, response, and recovery to disasters. DIS must monitor various disaster-related informations, keep various human resources and various material resources, and response real disasters. The conventional DISs are insufficient for integrated situation analysis, real-time report and operation, and utilizing the expertise of disaster personnels. In this study, the information-fusion based DIS framework is proposed for analysing various level informations, providing integrated situation informations and response plans, and processing real-time reports and operation according to field situations. The proposed DIS framework adopts information-fusion technologies and knowledge-based BRMS(Business Rule Management System).

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Implementation of Wavelet Transform based Image Fusion and JPEG2000 using MAD Order Statistics for Multi-Image (MAD 순서통계량을 이용한 웨이블렛 변환기반 다중영상의 영상융합 및 JPEG2000 보드 구현)

  • Lee, Cheeol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.11
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    • pp.2636-2644
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    • 2013
  • This paper is proposed a wavelet-based the order statistics MAD(Median Absolute Deviation) method of image fusion of Multi-image contaminated with visible image and infrared image. also The method of compared and defined the threshold the wavelet coefficients using MAD of the wavelet coefficients of the detail subbands was proposed to effectively fusion which of selected the high quality image of the two images. The existed fusion rule may be possible to get the distorted fusion image especially by the distortion in the relation between the pixel and indicator of two images in the existed fusion rules. In order to complement the disadvantage, the threshold of the proposed method sets up the image statistic and excludes the distortion. The hardware design is used FPGA of Xilinx and DSP system for the image fusion and compressed encoding of the proposed algorithm. Therefore the proposed method is totally verified by comparing with the several other multi-image and the proposed image fusion.

Channel Sensing Algorithm of Cognitive Radio Using by Multiple Antenna Receiving Technique (다중 안테나 수신 기법을 이용한 인지무선통신의 채널 센싱 기법)

  • Ryu, Je-Won;Kim, Jong-Ho;Choi, Young-Wan;Park, Ho-Hyun;Lee, Jeong-Woo;Kwon, Young-Bin;Park, Jae-Hwa
    • 한국정보통신설비학회:학술대회논문집
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    • 2009.08a
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    • pp.344-348
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    • 2009
  • Cognitive Radio(CR)는 특정 주파수 대역을 사용하도록 할당된 유저가 사용하지 않을 때, 이를 탐지하여 해당 주파수 대역을 이용함으로써 주파수 스펙트럼 효율을 향상시킬 수 있는 기술이다. 특히, CR에서 스펙트럼 센싱(Spectrum Sensing)은 중요한 기술의 하나라고 말할 수 있다. 기존의 스펙트럼 센싱 성능을 향상시키기 위한 방법으로, 다수의 노드가 각각 판정한 결과를 이용하는 OR-Rule, AND-Rule 등의 기법이 제안된 바 있다. 본 논문에서는 수신 다이버시티 기법 중의 하나인 Equal Gain Combiner(EGC) 알고리듬 이용하여 스펙트럼 센싱 성능을 알아보고 특히, 기존의 방법은 각 노드에서 판정 후 판정부에서 그 결과를 결합하여 최종 판정하는 방법이나, 본 논문에서 적용한 EGC 기법은 각 노드에서 수신된 신호에 대한 검출된 에너지 값을 융합센터(Fusion Center)로 보내어 최종 판정하는 방법이다. 각 노드에서 검출된 에너지 값을 융합센터가 수신한 신호에는 실질적으로 잡음이 섞이게 되므로 이로 인하여 발생할 수 있는 전송 오류를 추가적으로 고려하였다. 또한, 각 노드에서 검출한 에너지 값이 융합센터로 전송될 때에는 양자화 되어서 전송된다. 이에 따라서 양자화 bit수와 관련된 센싱 성능과 데이터의 반복 전송의 필요성, 그리고 그 횟수에 대해 제시하고자 한다.

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Adaptive Cooperative Spectrum Sensing Based on SNR Estimation in Cognitive Radio Networks

  • Ni, Shuiping;Chang, Huigang;Xu, Yuping
    • Journal of Information Processing Systems
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    • v.15 no.3
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    • pp.604-615
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    • 2019
  • Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.