• Title/Summary/Keyword: matching pursuit

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A Study on Matching Pursuit Interpolation with Moveout Correction (시간차 보정을 적용한 Matching Pursuit 내삽 기법 연구)

  • Lee, Jaekang;Byun, Joongmoo;Seol, Soon Jee;Kim, Young
    • Geophysics and Geophysical Exploration
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    • v.21 no.2
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    • pp.103-111
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    • 2018
  • The recent research aim of seismic trace interpolation is to effectively interpolate the data with spatial aliasing. Among various interpolation methods, the Matching Pursuit interpolation, that finds the proper combination of basis functions which can best recover traces, has been developed. However, this method cannot interpolate aliased data. Thus, the multi-component Matching Pursuit interpolation and moveout correction method have been proposed for interpolation of spatially aliased data. It is difficult to apply the multi-component Matching Pursuit interpolation to interpolating the OBC (Ocean Bottom Cable) data which is the multi-component data obtained at the ocean bottom because the isolation of P wave component is required in advance. Thus, in this study, we dealt with an effective single-component matching Pursuit interpolation method in OBC data where P-wave and S-wave are mixed and spatial aliasing is present. To do this, we proposed the Ricker wavelet based single-component Matching Pursuit interpolation workflow with moveoutcorrection and systematically investigated its effectiveness. In this workflow, the spatial aliasing problem is solved by applying constant value moveout correction to the data before the interpolation is performed. After finishing the interpolation, the inverse moveout correction is applied to the interpolated data using the same constant velocity. Through the application of our workflow to the synthetic OBC seismic data, we verified the effectiveness of the proposed workflow. In addition, we showed that the interpolation of field OBC data with severe spatial aliasing was successfully performed using our workflow.

Sinusoidal Modeling of Audio Signals Using Perceptually Weighted Matching Pursuit (지각적으로 가중된 매칭 퍼슈잇을 이용한 오디오 신호의 정현파 모델링)

  • 김연지;이인성
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.2
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    • pp.96-103
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    • 2003
  • This paper describes a method for sinusoidal modeling of audio signals using perceptually weighted matching pursuit. Matching pursuits extracts iteratively the greatest energy signals from the input signals until the residual between the original and the reconstructed signal is zero. In this paper, perceptual matching pursuits using psychoacoustic model to matching pursuit extracts greatest perceived energy iteratively. To evaluate the performance of the perceptual matching pursuits it is compared with the sinusoidal matching pursuits which is not included perceptual weighting. For various audio signals the result of simulation shows that the perceptual matching pursuit is superior to the sinusoidal matching pursuits, especially for a high change rate in time domain it can synthesized original signal.

Fast Matching Pursuit Using Absolute Symmetry and Classified Dictionary (절대값 대칭성과 사전 분류를 이용한 고속 Matching Pursuit)

  • O, Seok-Byeong;Jeon, Byeong-U
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.2
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    • pp.11-21
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    • 2002
  • Although the matching Pursuit is effective for video coding at low bit rate, it has a Problem since it needs much more calculation than the conventional block-based video coding method. The proposed fast matching pursuit method reduces inner product calculation that takes the most part of entire calculation by utilizing the symmetry of the absolute values of the one-dimensional Gator dictionary bases, the modified dictionary which allows faster matching without causing image quality degradation, and a Property of the two-dimensional Gabor dictionary that can be grouped in advance to four classes according to its frequency characteristics. Proposed method needs only about 1/8 of multiplications compared to the well-known separability-based fast method proposed by Neff.

Magnetic Resonance Imaging Using Matching Pursuit (Matching Pursuit 방법을 이용한 MR영상법에 관한 연구)

  • Ro, Y.M.;Zakhora, Avideh
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.05
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    • pp.230-234
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    • 1997
  • The matching pursuit (MP) algorithm developed by S. Mallat and Z. Zhang is applied to magnetic resonance (MR) imaging. Since matching pursuit is a greedy algorithm to find waveforms which are the best match for an object-signal, the signal can be decomposed with a few iterations. In this paper, we propose an application of the MP algorithm to the MR imaging to reduce imaging time. Inner products of residual signals and selected waveforms in the MP algorithm are derived from the MR signals by excitation of RF pulses which are fourier transforms of selected waveforms. Results from computer simulations demonstrate that the imaging time is reduced by using the MP algorithm and further a progressive reconstruction can be achieved.

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Multiple Candidate Matching Pursuit (다중 후보 매칭 퍼슛)

  • Kwon, Seokbeop;Shim, Byonghyo
    • Journal of Broadcast Engineering
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    • v.17 no.6
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    • pp.954-963
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    • 2012
  • As a greedy algorithm reconstructing the sparse signal from underdetermined system, orthogonal matching pursuit (OMP) algorithm has received much attention. In this paper, we multiple candidate matching pursuit (MuCaMP), which builds up candidate support set in every iteration and uses the minimum residual at last iteration. Using the restricted isometry property (RIP), we derive the sufficient condition for MuCaMP to recover the sparse signal exactly. The MuCaMP guarantees to reconstruct the K-sparse signal when the sensing matrix satisfies the RIP constant ${\delta}_{N+K}<\frac{\sqrt{N}}{\sqrt{K}+3\sqrt{N}}$. In addition, we show a recovery performance both noiseless and noisy measurements.

Fine Granular Scalable Coding using Matching Pursuit with Multi-Step Search (다단계 탐색 기반 Matching Pursuit을 이용한 미세 계층적 부호화 기법)

  • 최웅일
    • Journal of Broadcast Engineering
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    • v.6 no.3
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    • pp.225-233
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    • 2001
  • Real-time video communication applications over Internet should be able to support such functionality as scalability because of the unpredictable and varying channel bandwidth between server and client. To accommodatethe wide variety of channel bitrates, a new scalable coding tool, namely the Fine Granular Scalability (FGS) coding tool has been reduce the adopted In the MPEG-4 video standard. This paper presentsa new FGS algorithm with matching Pursuit that can reduce the computational complexity of ordinal matching pursuit-based algorithm. The Proposed coding algorithm can make trade-off between Picture Quality and computationalcomplexity. Our simulation result shows that the proposed algorithm can reduce the computational cumplexity up to 1/5 compared to the conventional FGS method while retaining a similar picture quality.

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Computational performance and accuracy of compressive sensing algorithms for range-Doppler estimation (거리-도플러 추정을 위한 압축 센싱 알고리즘의 계산 성능과 정확도)

  • Lee, Hyunkyu;Lee, Keunhwa;Hong, Wooyoung;Lim, Jun-Seok;Cheong, Myoung-Jun
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.5
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    • pp.534-542
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    • 2019
  • In active SONAR, several different methods are used to detect range-Doppler information of the target. Compressive sensing based method is more accurate than conventional methods and shows superior performance. There are several compressive sensing algorithms for range-Doppler estimation of active sonar. The ability of each algorithm depends on algorithm type, mutual coherence of sensing matrix, and signal to noise ratio. In this paper, we compared and analyzed computational performance and accuracy of various compressive sensing algorithms for range-Doppler estimation of active sonar. The performance of OMP (Orthogonal Matching Pursuit), CoSaMP (Compressive Sampling Matching Pursuit), BPDN (CVX) (Basis Pursuit Denoising), LARS (Least Angle Regression) algorithms is respectively estimated for varying SNR (Signal to Noise Ratio), and mutual coherence. The optimal compressive sensing algorithm is presented according to the situation.

Matching Pursuit Sinusoidal Modeling with Damping Factor (Damping 요소를 첨가한 매칭 퍼슈잇 정현파 모델링)

  • Jeong, Gyu-Hyeok;Kim, Jong-Hark;Lim, Joung-Woo;Joo, Gi-Ho;Lee, In-Sung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.1
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    • pp.105-113
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    • 2007
  • In this paper, we propose the matching pursuit with damping factors, a new sinusoidal model improving the matching pursuit, for the codecs based on sinusoidal model. The proposed model defines damping factors by using a correlativity of parameters between the current and adjacent frame, and estimates sinusoidal parameters more accurately in analysis frame by using the matching pursuit according to damping factor, and synthesizes the final signal. Then it is possible to model efficiently without interpolation schemes. The proposed sinusoidal model shows a better speech quality without an additional delay than the conventional sinusoidal model with interpolation methods. Through the SNR(signal to noise ratio), the MOS(Mean Opinion Score), LR(Itakura-Saito likelihood ratio), and CD(cepstral distance), we compare the performance of our model with that of matching pursuit using interpolation methods.

Wavelet Based Matching Pursuit Method for Interpolation of Seismic Trace with Spatial Aliasing (공간적인 알리아싱을 포함한 탄성파 트레이스의 내삽을 위한 요소파 기반의 Matching Pursuit 기법)

  • Choi, Jihun;Byun, Joongmoo;Seol, Soon Jee
    • Geophysics and Geophysical Exploration
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    • v.17 no.2
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    • pp.88-94
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    • 2014
  • Due to mechanical failure or geographical accessibility, the seismic data can be partially missed. In addition, it can be coarsely sampled such as crossline of the marine streamer data. This seismic data that irregular sampled and spatial aliased may cause problems during seismic data processing. Accurate and efficient interpolation method can solve this problem. Futhermore, interpolation can save the acquisition cost and time by reducing the number of shots and receivers. Among various interpolation methods, the Matching Pursuit method can be applied to any sampling type which is regular or irregular. However, in case of using sinusoidal basis function, this method has a limitation in spatial aliasing. Therefore, in this study, we have developed wavelet based Matching Pursuit method that uses wavelet instead of sinusoidal function for the improvement of dealiasing performance. In addition, we have improved interpolation speed by using inner product instead of L-2 norm.

Generalized Orthogonal Matching Pursuit (일반화된 직교 매칭 퍼슛 알고리듬)

  • Kwon, Seok-Beop;Shim, Byong-Hyo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.2
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    • pp.122-129
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    • 2012
  • As a greedy algorithm reconstructing the sparse signal from underdetermined system, orthogonal matching pursuit (OMP) algorithm has received much attention in recent years. In this paper, we present an extension of OMP for pursuing efficiency of the index selection. Our approach, referred to as generalized OMP (gOMP), is literally a generalization of the OMP in the sense that multiple (N) columns are identified per step. Using the restricted isometry property (RIP), we derive the condition for gOMP to recover the sparse signal exactly. The gOMP guarantees to reconstruct sparse signal when the sensing matrix satisfies the RIP constant ${\delta}_{NK}$ < $\frac{\sqrt{N}}{\sqrt{K}+2\sqrt{N}}$. In addition, we show recovery performance and the reduced number of iteration required to recover the sparse signal.