• 제목/요약/키워드: Multi-Propagation

검색결과 680건 처리시간 0.03초

MHCOC를 사용한 다중 부호 대역 확산 시스템과 적응성에 관한 연구 (A study on Multi-code Spread Spectrum System and its adaptation using MHCOC)

  • 공형윤;남두희
    • 정보처리학회논문지C
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    • 제12C권6호
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    • pp.901-906
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    • 2005
  • 본 논문에서는 초고속 전승을 위해 제안된 HCOC(High Capacity Orthogonal Code) 대역확산(Spread Spectrum) 시스템의 높은 PAPR(Peak power to Average Power Ratio)을 줄여주는 새로운 MHCOC (Mapped HCOC) 대역확산 기술을 제안하고, 같은 비트 수를 전송할 수 있는 기존의 MQAM 대역확산 시스템과 비교 분석한다. 또한 전송 채널의 상황에 따라 알맞은 데이터 서비스를 하는 QoS (Quality of Service)를 만족시키기 위해 제안한 시스템의 적응성에 대하여 연구한다. 컴퓨터 시뮬레이션을 통하여 제안한 시스템의 성능을 평가 및 분석하고, 기존의 시스템과 비교 분석한다.

A Multi-Level Integrator with Programming Based Boosting for Person Authentication Using Different Biometrics

  • Kundu, Sumana;Sarker, Goutam
    • Journal of Information Processing Systems
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    • 제14권5호
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    • pp.1114-1135
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    • 2018
  • A multiple classification system based on a new boosting technique has been approached utilizing different biometric traits, that is, color face, iris and eye along with fingerprints of right and left hands, handwriting, palm-print, gait (silhouettes) and wrist-vein for person authentication. The images of different biometric traits were taken from different standard databases such as FEI, UTIRIS, CASIA, IAM and CIE. This system is comprised of three different super-classifiers to individually perform person identification. The individual classifiers corresponding to each super-classifier in their turn identify different biometric features and their conclusions are integrated together in their respective super-classifiers. The decisions from individual super-classifiers are integrated together through a mega-super-classifier to perform the final conclusion using programming based boosting. The mega-super-classifier system using different super-classifiers in a compact form is more reliable than single classifier or even single super-classifier system. The system has been evaluated with accuracy, precision, recall and F-score metrics through holdout method and confusion matrix for each of the single classifiers, super-classifiers and finally the mega-super-classifier. The different performance evaluations are appreciable. Also the learning and the recognition time is fairly reasonable. Thereby making the system is efficient and effective.

MLS 가스겔용 NBR 피복 SUS301 박판의 피로파손 (Fatigue Fracture of NBR-coated SUS301 Thin Plate for MLS Gasket)

  • 한병기;조성산;장훈;김범근
    • 한국자동차공학회논문집
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    • 제12권4호
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    • pp.207-212
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    • 2004
  • Full-beads of multi-layer steel engine head gaskets that are used to seal the combustion gas between the head and the block are subject to cyclic bending stresses due to the variation of the head/block gap during engine operation. The S-N curve for the fatigue durability assessment of the full-bead formed on NBR-coated SUS301 thin plate is deduced from the axial fatigue test results because of the difficulty in conducting the bending fatigue test of thin plate. The experimental verification of the deduced S-N curve is presented. It is shown that the NBR coating increases the endurance limit of the plate significantly. Mechanism of crack nucleation and propagation in the full-bead is discussed with photographs of the fatigue cracks.

하이브리드 퍼지뉴럴네트워크의 알고리즘과 구조 (Algorithm and Architecture of Hybrid Fuzzy Neural Networks)

  • 박병준;오성권;김현기
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.372-372
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    • 2000
  • In this paper, we propose Neuro Fuzzy Polynomial Networks(NFPN) based on Polynomial Neural Network(PNN) and Neuro-Fuzzy(NF) for model identification of complex and nonlinear systems. The proposed NFPN is generated from the mutually combined structure of both NF and PNN. The one and the other are considered as the premise part and consequence part of NFPN structure respectively. As the premise part of NFPN, NF uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. As the consequence part of NFPN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. NFPN is available effectively for multi-input variables and high-order polynomial according to the combination of NF with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. In order to evaluate the performance of proposed models, we use the nonlinear function. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously.

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동영상 전송을 위한 채널 예측과 적응적 오류정정 부호화 기법 (Channel Estimation and Adaptive Channel Coding Technique for Video Transmission)

  • 송정선;이창우
    • 한국통신학회논문지
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    • 제29권5A호
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    • pp.492-501
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    • 2004
  • 압축된 동영상을 이동통신 채널과 같은 다경로 페이딩 채널을 통해서 전송할 때 전송오류에 의해서 전송 신호의 왜곡이 발생한다. 이러한 전송 오류를 줄이기 위한 한 가지 방법으로 오류정정 부호를 사용할 수 있다. 본 논문에서는 전송되는 정보의 단위인 프레임별로 채널의 상태를 예측하고 예측된 정보를 이용하여 RCPC(rate compatible punctured convolutional) 오류정정 부호의 부호화율을 적응적으로 변화시키는 방법을 제안한다. 이를 위하여 시변 페이딩 채널을 모델링하고 채널예측을 위한 3가지 방법을 제안하여 기존의 채널 예측 방법과 비교하고 성능을 분석하였다. 성능평가 결과 제안하는 적응적 오류정정 부호화 기법이 고정 부호화율을 갖는 오류정정 부호화 기법에 비해서 우수한 성능을 보임을 입증하였다.

신경회로망 모델을 이용한 철도 현가장치 설계변수 최적화 (Optimization of Design Variables of Suspension for Train using Neural Network Model)

  • 김영국;박찬경;황희수;박태원
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 춘계학술대회논문집
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    • pp.1086-1092
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    • 2002
  • Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.

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다층세라믹 콘덴서에서 생성된 크랙의 관찰과 분석 (Investigation and Analysis of Cracks in Multi-layer Ceramic Capacitor)

  • 이철승;강병성;허강헌;박진우
    • 한국세라믹학회지
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    • 제46권2호
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    • pp.211-218
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    • 2009
  • For the Y5V characteristic MLCC which is very prone to crack, it is important to to find out the basic cause of the crack. After finding out the crack origin, the materials and processes should be developed to remove the crack. The microstructures of the cracks were investigated using the fractographic method for the various types of cracks such as an exterior crack, a cyclic thermal shock crack, and an piezo-electric crack. It was found out that the crack origin was the pore at the end of the Ni inner electrode after bake-out. Even though the three dimensional crack shapes were different, the crack origins were seemed to be similar. The exterior crack could grow from the origin with the aids of residual and applied stress. FEM (finite element method) analysis was used to calculate the stress distribution of residual and applied stress. And the concept of fracture mechanics was applied for the explanation of the crack initiation and propagation from the stresses concentration.

역전파 선경회로망의 인식성능 향상에 관한 연구 (On the Enhancement of the Recognition Performance for Back Propagation Neural Networks)

  • 홍봉화;이지영
    • 한국컴퓨터정보학회논문지
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    • 제4권4호
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    • pp.86-93
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    • 1999
  • 본 논문에서는 다중 모듈러 신경회로망과 보상입력 알고리즘을 제안하였다. 전자는 신경회로망의 고질적인 문제중의 하나인 수렴속도의 감소를 위하여 제안하였고, 후자는 신경회로망의 인식수행능력 향상을 도모하기 위하여 제안하였다. 본 논문의 실험구성은 두 가지 형태와 시뮬레이션으로 나누어 구성하였다. 첫째로 다중 신경회로망의 구조에 한글, 영문자 와 숫자를 적용하여 인식 실험하였다. 둘째로, 보상입력 알고리즘과 보상입력을 결정하는 단계를 기술하였다. 제안된 알고리즘을 한글, 영문자. 숫자인식에 적용하여 기존의 신경회로망과 비교 평가하였다. 실험결과. 본 논문에서 제안된 모듈러 신경회로망이 기존의 신경회로망에 비하여 3배 이상 수렴속도가 개선되었고 보정입력 알고리즘을 적용한 다중 모듈러 신경회로망은 기존의 신경회로망에 비하여 10%정도 인식률이 향상됨을 고찰하였다.

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SEA를 이용한 쉘과 실린더의 최적 용접 조건에 관한 연구 (Study on Optimum Welding Position between Shell and Cylinder based on SEA.)

  • 안병하;이장우;양보석
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 춘계학술대회논문집
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    • pp.969-972
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    • 2003
  • The overall aim of this paper is to determine coupling loss factor of welding point between shell and cylinder using loss factor and structural loss factor. For this purpose, two kinds of loss factor were adopted. One is loss factor of each sub structure, another is structural loss factor based on the complex welded or assembled structure. Using these two parameters, it is possible to derive the coupling loss factor which represent characteristic condition of SEA theory. Coupling loss factor of conjunction in complex structure was expressed as power balance equation. The derived equation for a coupling loss factor has been simplified on the assumption of one way(nl- directional) power flow between multi-sub structures. Using these conditions, it is possible to find the equation of coupling loss factor expressed as above two loss factors. To check the effectiveness of above equation, this paper used two stage application. The first approach was application between simple cylinder and shell. The next was adopted rotary compressor. Rotary compressor has three main conjunctions between shell and internal vibration part. This equation was applied to find out the optimum welding Point with respect to reduce the noise propagation. It shows the effective tool to evaluate the coupling loss factor in complex structure

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표면파 분산특성과 전기비저항 분포특성에 대한 인접구조물의 영향 (Influence of Adjacent Structures on Surface-Wave Dispersion Characteristics and 2-D Resistivity Structure)

  • 조성호;김봉찬;조미라;김석철;윤대희;홍재호
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2008년도 추계 학술발표회
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    • pp.1318-1327
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    • 2008
  • Geotechnical sites in urban areas may have embedded structures such as utility lines and underground concrete structures, which cause difficulties in site investigation. This study is a preliminary research to establish knowledge base for developing an optimal technique for site investigation in urban areas. Surface-wave method and resistivity survey, which are frequently adopted for non-destructive site-investigation for geotechnical sites, were investigated to characterize effects of adjacent structures. In case of surface wave method, patterns of wave propagation were investigated for typical sets of multi-layered geotechnical profiles by numerical simulation based on forward modeling theory and field experiments for small-size model tests and real-scale tests in the field. In case of resistivity survey, 3-D finite element analyses and field tests were performed to investigate effects of adjacent concrete structures. These theoretical and experimental researches for surface-wave method and resistivity survey resulted in establishing physical criteria to cause interference of adjacent structures in site investigation at urban areas.

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