• Title/Summary/Keyword: Best approximation

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Resolution Improvement of Ultrasound Signal Using Kalman Filter (칼만 필터를 이용한 초음파 신호의 해상력 향상)

  • Woo, Kwang-B.;Nam, Sang-E.;Shin, Dong-H.;Chin, Young-M.;Lee, Sung-M.
    • Proceedings of the KOSOMBE Conference
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    • v.1985 no.06
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    • pp.15-19
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    • 1985
  • This study deals with a kind of signal processing, Kalman filtering techniques, which are applied to ultrasound signal to improve resolution capability. The main advantage of Kalman filter algorithm for the analysis of reflected ultrasound signal is its recursive structure which can be easily adapted to time-varing system. In state-space description of the system, the 6th order system produces the best spectral approximation to the source pulse. As a result of spectrum analysis, 6th order estimator for two closely spaced (0.5mm) reflectors enhance resolution by 4dB - 10dB. By using this result, the possibility to detect even minute tumor is found.

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Study on Energy Distribution of the 6 MeV Electron Beam using Gaussian Approximation (가우시안 근사를 이용한 6 MeV 전자선의 에너지분포에 관한 연구)

  • Lee, Jeong-Ok;Kim, Seung-Kon
    • Journal of radiological science and technology
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    • v.22 no.2
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    • pp.53-56
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    • 1999
  • A Gaussian distribution was parametrized for the initial distribution of the electron beam emitted from a 6MeV medical linear accelerator. A percent depth dose was measured in a water phantom and the corresponding Monte Carlo calculations were performed starting from a Gaussian distribution for a range of standard deviations, ${\sigma}=0.1$, 0.15, 0.2, 0.25, and 0.3 with being the mean value for the Incident beam energy. When measurement and calculation were compared, the calculation with the Gaussian distribution for ${\sigma}=0.25$ turned out to agree best with the measurement. The results from the present work can be utilized as input energy data in planning an electron beam therapy with a Monte Carlo calculation.

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Development of an optimal measuring device selection system using neural networks (Neural Network을 이용한 최적 측정장비 결정 시스템 개발)

  • 손석배;박현풍;이관행
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.11a
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    • pp.299-302
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    • 2000
  • Various types of measuring devices are used for reverse engineering and inspection in different fields of industry such as automotive, aerospace, computer graphics, and home appliance. In order to measure a part easily and efficiently, it is important to select appropriate measuring device considering the characteristics of each measuring machine and part information. In this research, an optimal measuring device selection system using neural networks is proposed. There are two major steps: Firstly, the measuring information such as curvature, normal, type of surface, edge, and facet approximation is extracted from the CAD model. Second, the best suitable measuring device is proposed using the neural network system based on the knowledge of the measuring parameters and the measuring resources. An example of machine selection is implemented to evaluate the performance of the system.

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Comparison of the Normalized SNRs between the LPA Beamformer and the Conventional Beamformer for a Moving Source

  • Seokjin Sung;Hyunduk Kang;Kim, Kiseon
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.190-193
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    • 2003
  • The DOA(Direction Of Arrival) estimation to select a best beam for receiving a particular signal in switched beam antenna systems, and to shape the optimal beam in adaptive array antenna systems, is typically performed under the assumption that the target user motion is almost negligible. In this paper, we model the user as the time-varying source and adopt the LPA(Local Polynomial Approximation) tracking algorithm, proposed by Katkovnik, to solve the time-varying DOA estimation problem. Then, we compare the power spectrum functions between the LPA beamformer and the conventional beamformer, also, the normalized SNRs of each beamformer. The results show that the LPA beamformer is robuster than the conventional beamformer in tine-varying environments. In addition, in case of the conventional beamformer, more array elements give rise to more degradation in the aspect of SNR.

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Reduced-order Controller Design using Projective Controls (투영제어 기법을 이용한 제어기의 저차수화 설계)

  • Sang-Woo Nam
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.7
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    • pp.943-951
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    • 1995
  • In this paper the projective controls, previously derived to preserve the dynamic modes of a state-feedback reference system, are extended to allow the preservation of the modes of a general output-feedback reference system. In general, the extension allows projective controls to be used as a controller approximation technique, where a reduced-order controller is designed to approximate the closed-loop behavior of the higher-order reference controller. This extension is useful if the best available reference control for the system is an output-feedback control. An example shows that the increased design freedom of proposed design method allows the stabilization of a given plant using a lower-order controller than the projective controls with state-feedback reference.

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Optimized Algebra LDPC Codes for Bandwidth Efficient Modulation

  • Hwang, Gi-Yean;Yu Yi;Lee, Moon-Ho
    • Journal of electromagnetic engineering and science
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    • v.4 no.1
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    • pp.17-22
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    • 2004
  • In this paper, we implement an efficient MLC/PDL system for AWGN channels. In terms of the tradeoff between the hardware implementation and system performance, proposed algebra LDPC codes are optimized by the Gaussian approximation(GA) according to the rate of each level assigned by the capacity rule and chosen as the component code. System performance with Ungerboeck Partitioning(UP), Miked Partitioning(MP) and Gray Mapping(GM) of 8PSK are evaluated, respectively. Many results are presented in this paper; they can indicate that the proposed MLC/PDL system using optimized algebra LDPC codes with different code rate, capacity rule and Gray mapping(GM) can achieve the best performance.

Preliminary Research on the Uncertainty Estimation in the Probabilistic Designs

  • Youn Byung D.;Lee Jae-Hwan
    • Journal of Ship and Ocean Technology
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    • v.9 no.1
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    • pp.64-71
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    • 2005
  • In probabilistic design, the challenge is to estimate the uncertainty propagation, since outputs of subsystems at lower levels could constitute inputs of other systems or at higher levels of the multilevel systems. Three uncertainty propagation estimation techniques are compared in this paper in terms of numerical efficiency and accuracy: root sum square (linearization), distribution-based moment approximation, and Taguchi-based integration. When applied to reliability-based design optimization (RBDO) under uncertainty, it is investigated which type of applications each method is best suitable for. Two nonlinear analytical examples and one vehicle crashworthiness for side-impact simulation example are employed to investigate the unique features of the presented techniques for uncertainty propagation. This study aims at helping potential users to identify appropriate techniques for their applications in the multilevel design.

Intelligent system using frame function in wavelet neural network (웨이브릿 신경회로망의 프레임 함수를 이용한 지능시스템)

  • 홍석우;김용택;연정흠;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.05a
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    • pp.195-198
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    • 2000
  • We propose a new wavelet neural network structure, for which we apply new recurrent nodes to the network, in this paper for the dynamic system identification and control. We will construct the wavelet neural network by using wavelet frame function. The function does not have the best approximation property, but it may be possible to apply some modification to the structure of the network because the constriction of orthogonality is loosened a little. This wavelet neural network we propose can obtain previous state information by its structure of the network without any addition of input, though the conventional wavelet network needs additional previous state input for the improvement of the dynamic performance. In numerical experience, the performance of the new wavelet neural network we propose in the nonlinear system with uncertainity of parameter Is equal to that of the wavelet network which used the additional previous information input, superior to that of the conventional wavelet network.

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Utterance Verification Using Search Confusion Rate and Its N-Best Approach

  • Kim, Kyu-Hong;Kim, Hoi-Rin;Hahn, Min-Soo
    • ETRI Journal
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    • v.27 no.4
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    • pp.461-464
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    • 2005
  • Recently, a variety of confidence measures for utterance verification has been studied to improve speech recognition performance by rejecting out-of-vocabulary inputs. Most of the conventional confidence measures for utterance verification are based primarily on hypothesis testing or an approximated posterior probability, and their performances depend on the robustness of an alternative hypothesis or the prior probability. We introduce a novel confidence measure called a search confusion rate (SCR), which does not require an alternative hypothesis or the approximation of posterior probability. Our confusion-based approach shows better performance in additive noise-corrupted speech as well as in clean speech.

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Dynamic analysis of 3-D structures with adaptivity in RBF of dual reciprocity BEM

  • Razaee, S.H.;Noorzad, A.
    • Structural Engineering and Mechanics
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    • v.29 no.2
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    • pp.117-134
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    • 2008
  • A new adaptive dual reciprocity boundary element method for dynamic analysis of 3-D structures is presented in this paper. It is based on finding the best approximation function of a radial basis function (RBF) group $f=r^n+c$ which minimize the error of displacement field expansion. Also, the effects of some parameters such as the existence of internal points, number of RBF functions and position of collocation nodes in discontinuous elements are investigated in this adaptive procedure. Three numerical examples show improvement in dynamic response of structures with adaptive RBF in dual reciprocity with respect to ordinary BEM.