• 전자공학회논문지
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• 제54권8호
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• pp.12-19
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• 2017

본 논문에서는 희박신호 (sparse signal) 기법을 이용하여 대역확산 (spread spectrum) 신호의 지연시간을 추정하는 초 분해능 지연시간 추정 방식을 제안한다. 지금까지 대역확산 신호의 지연시간 추정은 코릴레이션 방식이 주로 이용되어 왔으나 이 방식은 신호들이 한 PN 칩(pseudo-noise chip) 이내의 시간 차로 입사하는 경우에는 지연시간을 정확히 추정할 수 없으며 보다 정확한 추정을 위해 코릴레이션 출력에 대한 추가적인 프로세싱이 필요하다. 최근 들어 희박 신호 (sparse signal) 알고리즘이 도래각 추정 분야에서 각광을 받고 있으며 그 중 SPICE 알고리즘이 가장 대표적이다. 따라서, 본 논문에서는 SPICE 알고리즘을 이용하는 초 분해능 지연시간 추정 알고리즘을 개발하고 ISO/IEC 24730-2.1 RTLS 시스템에 적용하여 MUSIC 알고리즘과 성능을 비교, 분석한다.

• Structural Engineering and Mechanics
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• 제91권2호
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• pp.227-238
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• 2024

Sparse regularization methods have proven effective in addressing the ill-posed equations encountered in moving force identification (MFI). However, the complexity of vehicle loads is often ignored in existing studies aiming at enhancing MFI accuracy. To tackle this issue, a double 𝑙₁ regularization method is proposed for MFI based on a response spectrum-based weighted dictionary in this study. Firstly, the relationship between vehicle-induced responses and moving vehicle loads (MVL) is established. The structural responses are then expanded in the frequency domain to obtain the prior knowledge related to MVL and to further construct a response spectrum-based weighted dictionary for MFI with a higher accuracy. Secondly, with the utilization of this weighted dictionary, a double 𝑙₁ regularization framework is presented for identifying the static and dynamic components of MVL by the alternating direction method of multipliers (ADMM) method successively. To assess the performance of the proposed method, two different types of MVL, such as composed of trigonometric functions and driven from a 1/4 bridge-vehicle model, are adopted to conduct numerical simulations. Furthermore, a series of MFI experimental verifications are carried out in laboratory. The results shows that the proposed method's higher accuracy and strong robustness to noises compared with other traditional regularization methods.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.559-568
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• 2017

Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/inter-harmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.

• ETRI Journal
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• 제39권1호
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• pp.21-29
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• 2017

This paper addresses the problem of unsupervised speech separation based on robust non-negative matrix factorization (RNMF) with ${\beta}$-divergence, when neither speech nor noise training data is available beforehand. We propose a robust version of non-negative matrix factorization, inspired by the recently developed sparse and low-rank decomposition, in which the data matrix is decomposed into the sum of a low-rank matrix and a sparse matrix. Efficient multiplicative update rules to minimize the ${\beta}$-divergence-based cost function are derived. A convolutional extension of the proposed algorithm is also proposed, which considers the time dependency of the non-negative noise bases. Experimental speech separation results show that the proposed convolutional RNMF successfully separates the repeating time-varying spectral structures from the magnitude spectrum of the mixture, and does so without any prior training.

• Nuclear Engineering and Technology
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• 제52권7호
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• pp.1495-1502
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• 2020

A new method of X-ray source spectrum estimation based on compressed sensing is proposed in this paper. The algorithm K-SVD is applied for sparse representation. Nonnegative constraints are added by modifying the L₁ reconstruction algorithm proposed by Rosset and Zhu. The estimation method is demonstrated on simulated spectra typical of mammography and CT. X-ray spectra are simulated with the Monte Carlo code Geant4. The proposed method is successfully applied to highly ill conditioned and under determined estimation problems with a good performance of suppressing noises. Results with acceptable accuracies (MSE < 5%) can be obtained with 10% Gaussian white noises added to the simulated experimental data. The biggest difference between the proposed method and the existing methods is that multiple prior knowledge of X-ray spectra can be included in one dictionary, which is meaningful for obtaining the true X-ray spectrum from the measurements.

• 한국통신학회논문지
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• 제38B권9호
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• pp.765-774
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• 2013

본 논문에서는 분산된 광대역 인지 무선 네트워크 환경에서 상관관계를 갖는 다중 신호를 위한 협력 압축 스펙트럼 센싱 기법을 제안한다. 압축 센싱 (Compressed Sensing)은 나이퀴스트율 (Nyquist Rate) 이하로 샘플링된 신호를 높은 확률로 복구할 수 있는 신호처리 기법으로 기존의 광대역 스펙트럼 센싱을 위해서 필요로 했던 고속의 아날로그-디지털 변환기 구현 문제를 해결할 수 있다. 압축 센싱에서는 압축된 신호를 원본 신호로 정확하게 복구하는 복구 알고리즘을 설계하는 것이 하나의 핵심 문제이다. 본 논문에서는 나이퀴스트율 이하로 압축된 신호의 복구 성능을 높이기 위하여 연속된 다중 입력 신호로 구성된 Multiple Measurement Vector 모델을 이용하였고, 입력 신호 사이의 시간적 상관관계를 이용하는 협력 베이지안 복구 알고리즘을 제안한다.

• 한국음향학회지
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• 제36권6호
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• pp.394-400
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• 2017

본 논문은 기존의 시간영역에서 다루던 공분산 행렬 fitting 기반 도래각 추정 알고리즘인 SpSF(Sparse Spectrum Fitting)를 주파수 영역으로 확장함으로써 기존의 시간영역의 SpSF 알고리즘이 주파수 영역에서도 구현 가능함을 보인다. 기존의 주파수 영역에서 구현되는 도래각 추정 알고리즘과의 성능 분석 및 비교를 통해 압축센싱 기반 공분산 fitting 알고리즘인 SpSF의 우수함을 보여준다.

• Current Optics and Photonics
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• 제8권1호
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• pp.38-44
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• 2024

Under the influence of atmospheric turbulence, a star's point image will shake back and forth erratically, and after exposure the originally small star point will spread into a huge spot, which will affect the ground calibration of the star sensor. To analyze the impact of atmospheric turbulence on the positioning accuracy of the star's center of mass, this paper simulates the atmospheric turbulence phase screen using a method based on a sparse spectrum. It is added to the static-star-simulation device to study the transmission characteristics of atmospheric turbulence in star-point simulation, and to analyze the changes in star points under different atmospheric refractive-index structural constants. The simulation results show that the structure function of the atmospheric turbulence phase screen simulated by the sparse spectral method has an average error of 6.8% compared to the theoretical value, while the classical Fourier-transform method can have an error of up to 23% at low frequencies. By including a simulation in which the phase screen would cause errors in the center-of-mass position of the star point, 100 consecutive images are selected and the average drift variance is obtained for each turbulence scenario; The stronger the turbulence, the larger the drift variance. This study can provide a basis for subsequent improvement of the ground-calibration accuracy of a star sensitizer, and for analyzing and evaluating the effect of atmospheric turbulence on the beam.

• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.435-443
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• 2007

Computing the interior spectrum of large sparse generalized eigenvalue problems $Ax\;=\;{\lambda}Bx$, where A and b are large sparse and SPD(Symmetric Positive Definite), is often required in areas such as structural mechanics and quantum chemistry, to name a few. Recently, CG-type methods have been found useful and hence, very amenable to parallel computation for very large problems. Also, as in the case of linear systems proper choice of preconditioning is known to accelerate the rate of convergence. After the smallest eigenpair is found we use the orthogonal deflation technique to find the next m-1 eigenvalues, which is also suitable for parallelization. This offers advantages over Jacobi-Davidson methods with partial shifts, which requires re-computation of preconditioner matrx with new shifts. We consider as preconditioners Incomplete LU(ILU)(0) in two variants, ever-relaxation(SOR), and Point-symmetric SOR(SSOR). We set m to be 5. We conducted our experiments on matrices from discretizations of partial differential equations by finite difference method. The generated matrices has dimensions up to 4 million and total number of processors are 32. MPI(Message Passing Interface) library was used for interprocessor communications. Our results show that in general the Multi-Color ILU(0) gives the best performance.

• The Korean Journal of Ecology
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• 제6권4호
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• pp.33-59
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• 1983

An investigation has been performed on the flora and life form of the vascular plants at Mt. Sori in Kwangneung from March to November in 1982. In a survey field trip, 539 species, 344 genera, 102 families of plants. are collected. Among them Hylomecon vernale, Aconitum coreanum, A. pseudoproliferum, Adonis amurensis, Anemone raddeana is important plant in this area and they are becoming sparse than past. In the life form spectrum hemiryptophytes is 40.6%.