• Title/Summary/Keyword: subspace method

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Structural Topology Optimization for the Natural Frequency of a Designated Mode

  • Lim, O-Kaung;Lee, Jin-Sik
    • Journal of Mechanical Science and Technology
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    • v.14 no.3
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    • pp.306-313
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    • 2000
  • The homogenization method and the density function method are common approaches to evaluate the equivalent material properties for design cells composed of matter and void. In this research, using a new topology optimization method based on the homogenized material with a penalty factor and the chessboard prevention strategy, we obtain the optimal layout of a structure for the natural frequency of a designated mode. The volume fraction of nodes of each finite element is chosen as the design variable and a total material usage constraint is imposed. In this paper, the subspace method is used to evaluate the eigenvalue and its corresponding eigenvector of the structure for the designated mode and the recursive quadratic programming algorithm, PLBA algorithm, is used to solve the topology optimization problem.

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An Efficient Face Recognition using Feature Filter and Subspace Projection Method

  • Lee, Minkyu;Choi, Jaesung;Lee, Sangyoun
    • Journal of International Society for Simulation Surgery
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    • v.2 no.2
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    • pp.64-66
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    • 2015
  • Purpose : In this paper we proposed cascade feature filter and projection method for rapid human face recognition for the large-scale high-dimensional face database. Materials and Methods : The relevant features are selected from the large feature set using Fast Correlation-Based Filter method. After feature selection, project them into discriminant using Principal Component Analysis or Linear Discriminant Analysis. Their cascade method reduces the time-complexity without significant degradation of the performance. Results : In our experiments, the ORL database and the extended Yale face database b were used for evaluation. On the ORL database, the processing time was approximately 30-times faster than typical approach with recognition rate 94.22% and on the extended Yale face database b, the processing time was approximately 300-times faster than typical approach with recognition rate 98.74 %. Conclusion : The recognition rate and time-complexity of the proposed method is suitable for real-time face recognition system on the large-scale high-dimensional face database.

A Study on Performance Improvement of Adaptive SLC System using Eigenanalysis Method (Eigenanalysis 방식을 이용한 적응 SLC(sidelobe canceller)시스템의 성능향상에 관한 연구)

  • 김세연;정신철;이병섭
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.12 no.5
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    • pp.694-704
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    • 2001
  • In this work, We evaluate the performance of eigencanceller which can suppress directional interferences and noise effectively while maintaining specified beam pattern constraints. The constraints and optimal weight vector of eigencanceller vary by using interference and noise or desired signal, interference and noise as array input signal. From the analysis results in the steady state, We show that weight vectors in each case are simplified the form of projection equation that belongs to desired subspace orthogonal to interference subspace and eigencanceller has the better performance than DMI method through mathematical analysis and simulation.

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L1-norm Regularization for State Vector Adaptation of Subspace Gaussian Mixture Model (L1-norm regularization을 통한 SGMM의 state vector 적응)

  • Goo, Jahyun;Kim, Younggwan;Kim, Hoirin
    • Phonetics and Speech Sciences
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    • v.7 no.3
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    • pp.131-138
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    • 2015
  • In this paper, we propose L1-norm regularization for state vector adaptation of subspace Gaussian mixture model (SGMM). When you design a speaker adaptation system with GMM-HMM acoustic model, MAP is the most typical technique to be considered. However, in MAP adaptation procedure, large number of parameters should be updated simultaneously. We can adopt sparse adaptation such as L1-norm regularization or sparse MAP to cope with that, but the performance of sparse adaptation is not good as MAP adaptation. However, SGMM does not suffer a lot from sparse adaptation as GMM-HMM because each Gaussian mean vector in SGMM is defined as a weighted sum of basis vectors, which is much robust to the fluctuation of parameters. Since there are only a few adaptation techniques appropriate for SGMM, our proposed method could be powerful especially when the number of adaptation data is limited. Experimental results show that error reduction rate of the proposed method is better than the result of MAP adaptation of SGMM, even with small adaptation data.

New Sound Spectral Analysis of Prosthetic Heart Valve (인공판막음의 새로운 스펙트럼 분석 연구)

  • Lee, H.J.;Kim, S.H.;Chang, B.C.;Tack, G.;Cho, B.K.;Yoo, S.K.
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.11
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    • pp.75-78
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    • 1997
  • In this paper we present new sound spectral analysis methods or prosthetic heart valve sounds. Phonocardiograms(PCG) of prosthetic heart valve were analyzed in order to derive frequency domain feature suitable or the classification of the valve state. The fast orthogonal search method and MUSIC (MUltiple SIgnal Classification) method are described or finding the significant frequencies in PCG. The fast orthogonal search method is effective with short data records and cope with noisy, missing and unequally-spaced data. MUSIC method's key to the performance is the division of the information in the autocorrelation matrix or the data matrix into two vector subspaces, one a signal subspace and the other a noise subspace.

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Direct position tracking method for non-circular signals with distributed passive arrays via first-order approximation

  • Jinke Cao;Xiaofei Zhang;Honghao Hao
    • ETRI Journal
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    • v.46 no.3
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    • pp.421-431
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    • 2024
  • In this study, a direct position tracking method for non-circular (NC) signals using distributed passive arrays is proposed. First, we calculate the initial positions of sources using a direct position determination (DPD) approach; next, we transform the tracking into a compensation problem. The offsets of the adjacent time positions are calculated using a first-order Taylor expansion. The fusion calculation of the noise subspace is performed according to the NC characteristics. Because the proposed method uses the signal information from the previous iteration, it can realize automatic data associations. Compared with traditional DPD and two-step localization methods, our novel process has lower computational complexity and provides higher accuracy. Moreover, its performance is better than that of the traditional tracking methods. Numerous simulation results support the superiority of our proposed method.

Frequency Response Analysis of Array-Type MEMS Resonators by Model Order Reduction Using Krylov Subspace Method (크리로프 부공간법에 근거한 모델차수축소기법을 통한 배열형 MEMS 공진기의 주파수응답해석)

  • Han, Jeong-Sam;Ko, Jin-Hwan
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.9
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    • pp.878-885
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    • 2009
  • One of important factors in designing MEMS resonators for RF filters is obtaining a desired frequency response function (FRF) within a specific frequency range of interest. Because various array-type MEMS resonators have been recently introduced to improve the filter characteristics such as bandwidth, pass-band, and shape factor, the degrees of freedom (DOF) of finite elements for their FRF calculation dramatically increases and therefore raises computational difficulties. In this paper the Krylov subspace-based model order reduction using moment-matching with non-zero expansion points is represented as a numerical solution to perform the frequency response analyses of those array-type MEMS resonators in an efficient way. By matching moments at a frequency around the specific operation range of the array-type resonators, the required FRF can be efficiently calculated regardless of their operating frequency from significantly reduced systems. In addition, because of the characteristics of the moment-matching method, a minimal order of reduced system with a prearranged accuracy can be determined through an error indicator using successive reduced models, which is very useful to automate the order reduction process and FRF calculation for structural optimization iterations. We also found out that the presented method could obtain the FRF of a $6\times6$ array-type resonator within a seventieth of the computational time necessary for the direct method and in addition FRF calculation by the mode superposition method could not even be completed because of a data overflow with a half after calculation of 9,722 eigenmodes.

Selective Subspace Interference Alignment for Cognitive Radio Systems (선택적 부분공간 간섭 정렬을 이용한 상황인식 시스템)

  • Cho, Hyung-Weon;Park, Jong-Hun;Hong, Suk-Jin;Seo, Jong-Pil;Chung, Jae-Hak;Chung, Jong-Moon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.6A
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    • pp.592-600
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    • 2011
  • This paper presents a selective interference alignment for cognitive radio system with spectrum leasing. The proposed method selects users who cause severe interference to other basestations that have required SINR. Since few users are selected to apply subspace interference alignment, the total complexity of the system is not high compared with that of the system who utilizes subspace interference alignment to all users. In addition, all users can transmit without considering interference. The computer simulation shows the proposed method exhibits 350% throughput enhancement at a two cell case, and 400% increase at a three cell case.

Face Illumination Normalization based on Illumination-Separated Face Identity Texture Subspace (조명영향 분리 얼굴 고유특성 텍스쳐 부분공간 기반 얼굴 이미지 조명 정규화)

  • Choi, Jong-Keun;Chung, Sun-Tae;Cho, Seong-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.1
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    • pp.25-34
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    • 2010
  • Robust face recognition under various illumination environments is difficult to achieve. For robust face recognition with respect to illumination variations, illumination normalization of face images is usually applied as a preprocessing step. Most of previously proposed illumination normalization methods cannot handle cast shadows in face images effectively. In this paper, We propose a new face illumination normalization method based on the illumination-separated face identity texture subspace. Since the face identity texture subspace is constructed so as to be separated from the effects of illumination variations, the projection of face images into the subspace produces a good illumination-normalized face images. Through experiments, it is shown that the proposed face illumination normalization method can effectively eliminate cast shadows as well as attached shadows and achieves a good face illumination normalization.

Subspace Method Based Precoding for MIMO Spatial Multiplexing (공간 다중화를 위한 부 공간 방식 Precoding 기법)

  • Mun Cheol;Jung Chang-Kyoo;Park DongHee;Kwak Yoonsik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.6
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    • pp.1161-1166
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    • 2005
  • In this paper, for spatial multiplexing with limited feedback, we propose subspace based precoding in which the active bases are selected at the receiver from a finite number of basis sets known at both receiving and transmitting ends, conveyed to the transmitter using limited feedback, and assembled into a preceding matrix at the transmitter. The selected bases are conveyed to the transmitter using feedback information on both the index of a basis set, which indicates the most appropriate set of coordinates for describing a MIMO channel, and the active bases having the significant amounts of energy in the selected basis set. We show that the proposed subspace based precoding provides capacity similar to that of the closed-loop MIMO even with limited feedback.