• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.7
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• pp.424-430
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• 2014

In this paper, we propose a compressed sensing-based signal recovery technique for an uplink multi-user spatial modulation (MU-SM) system. In the MU-SM system, only one antenna among $N_t$ antennas of each user becomes active by nature. Thus, this characteristics is exploited for signal recovery at a base station. We modify the conventional orthogonal matching pursuit (OMP) algorithm which has been widely used for sparse signal recovery in literature for the MU-SM system, which is called MU-OMP. We also propose a parallel OMP algorithm for the MU-SM system, which is called MU-POMP. Specifically, in the proposed algorithms, antenna indices of a specific user who was selected in the previous iteration are excluded in the next iteration of the OMP algorithm. Simulation results show that the proposed algorithms outperform the conventional OMP algorithm in the MU-SM system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.636-645
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• 2017

A scanning radar is exploited widely such as for ground surveillance, disaster rescue, and etc. However, the range resolution is limited by transmitted bandwidth and cross-range resolution is limited by beam width. In this paper, we propose a method for super-resolution radar imaging. If the distribution of reflectivity is sparse, the distribution is called sparse signal. That is, the problem could be formulated as compressive sensing problem. In this paper, 2D super-resolution radar image is generated via reweighted ${\ell}_1-Minimization$. In the simulation results, we compared the images obtained by the proposed method with those of the conventional Orthogonal Matching Pursuit(OMP) and Synthetic Aperture Radar(SAR).

• The Journal of the Acoustical Society of Korea
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• v.25 no.1
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• pp.21-29
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• 2006

In this Paper a split bandwidth wideband speech coder and its highband coding method are Proposed. The coder uses a split-band approach. where the wideband input speech signal is split into two equal frequency bands from 0-4kHz and 4-8kHz. The lowband and the highband are coded respectively by the 11.8kb/s G.729 Annex E and the proposed coding method. After the LPC analysis, the highband is divided by two modes according to the properties of signals. In stationary mode. the highband signals are compressed by the mixture excitation model; CELP algorithm and W (Matching Pursuit) algorithm. The others are coded by the only CELP algorithm. We compare the performance of the new wideband speech coder with that of G.722 48kbps SB-ADPCM and G.722.2 12.85kbps in a subjective method. The simulation results show that the Performance of the proposed wideband speech coder has better than that of 48kbps G.722 and no better than that of 12.85kbps G.722.2.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.53-76
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• 2020

The synchronous phasor measurement algorithm is the core content of the phasor measurement unit. This manuscript proposes a dynamic synchronous phasor measurement algorithm based on compressed sensing theory. First, a dynamic signal model based on the Taylor series was established. The dynamic power signal was preprocessed using a least mean square error adaptive filter to eliminate interference from noise and harmonic components. A Chirplet overcomplete dictionary was then designed to realize a sparse representation. A reduction of the signal dimension was next achieved using a Gaussian observation matrix. Finally, the improved orthogonal matching pursuit algorithm was used to realize the sparse decomposition of the signal to be detected, the amplitude and phase of the original power signal were estimated according to the best matching atomic parameters, and the total vector error index was used for an error evaluation. Chroma 61511 was used for the output of various signals, the simulation results of which show that the proposed algorithm cannot only effectively filter out interference signals, it also achieves a better dynamic response performance and stability compared with a traditional DFT algorithm and the improved DFT synchronous phasor measurement algorithm, and the phasor measurement accuracy of the signal is greatly improved. In practical applications, the hardware costs of the system can be further reduced.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.525-528
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• 2001

본 논문은 음성 및 음악을 위한 새로운 4kbps 다중 모드 하모닉 변환 여기 부호화 방법을 제안한다. 제안된 부호화방법은 음성/음악 분류기에 의해 분류된 신호를 각각 하모닉-잡음 여기모델과 MLT 여기모델로 부호화한다. 하모닉-잡음 여기모델에서는 전이구간과 유/무성음 혼합신호의 모델링오차 개선을 위해 MP(Matching Pursuit)방법과 혼합된 잡음스펙트럴을 표현하기 위한 캡스트럽 LPC 잡음 모델, 빠른 정현파 합성법을 제안한다. 음악에서는 비트할당 효율을 높이기위한 LP 적응 피크 분석을 적용한 MLT(Modulated Lapped Transform) 부호화 방법을 제안한다. 제안된 방법을 적용한 4kbps 음성부호화 방법은 전이구간에서의 향상된 모델링 구조를 보여주었으며, 주관적음질 평가 8kbps QCELP 보다 MOS 0.2 정도 향상된 결과를 얻었다.

• ETRI Journal
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• v.39 no.1
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• pp.1-12
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• 2017

In this paper, we present a new approach for the progressive compression of three-dimensional (3D) mesh geometry using redundant frame dictionaries and sparse approximation techniques. We construct the proposed frames from redundant linear combinations of the eigenvectors of a combinatorial mesh Laplacian matrix. We achieve a sparse synthesis of the mesh geometry by selecting atoms from a frame using matching pursuit. Experimental results show that the resulting rate-distortion performance compares favorably with other progressive mesh compression algorithms in the same category, even when a very simple, sub-optimal encoding strategy is used for the transmitted data. The proposed frames also have the desirable property of being able to be applied directly to a manifold mesh having arbitrary topology and connectivity types; thus, no initial remeshing is required and the original mesh connectivity is preserved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.580-592
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• 2012

In this paper, a new compressive feedback (CF) scheme based on distributed compressed sensing (DCS) for time-corrected MIMO channel is proposed. First, the channel state information (CSI) is approximated by using a subspace matrix, then, the approximated CSI is compressed using a compressive matrix. At the base station, the approximated CSI can be robust recovered with simultaneous orthogonal matching pursuit (SOMP) algorithm by using forgone CSIs. Simulation results show our proposed DCS-CF method can improve the reliability of system without creating a large performance loss.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.317-318
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• 2012

Sparse한 신호 복원 방법으로 underdetemined system에서 11-minimization을 이용한 compressive sensing의 연구와 함께, 11-minimization 비해 간단한 greed 알고리듬도 활발히 연구되고 있다. 이에 본 논문은 greed 알고리듬의 대표적인 orthogonal matching pursuit기법에서 iteration 마다 support 선택 개수에 따른 성능을 연구한다. 모의 실험을 통해 OMP의 iteration 단계에서 하나의 support만 선택하는 것보다 다수의 support를 선택하는 것이 더 낮은 sparsity의 신호를 복원할 수 있고 더 낮은 계산량의 이득을 가져오는 것을 확인 할 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.51-53
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• 2015

In this paper, we propose an efficient sparse signal recovery algorithm referred to as the matching pursuit with a tree pruning (TMP). Two key ingredients of TMP are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In our analysis, we show that the sparse signal is accurately reconstructed when the sensing matrix satisfies the restricted isometry property. In our simulations, we confirm that TMP is effective in recovering sparse signals and outperforms conventional sparse recovery algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.1-3
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• 2015

In this paper, we propose a sparse signal reconstruction method referred to as the matching pursuit with a pruning-based tree search (PTS-MP). Two key ingredients of PTS-MP are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In our simulations, we confirm that PTS-MP is effective in recovering sparse signals and outperforms conventional sparse recovery algorithms.