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심병효 空軍士官學校 1998 論文集 Vol.41 No.-
digital image halftoning is the process of converting grey-scale image into a form suitable for display on binary devices such as laser printers or inkjet printers. After proper halfoning process, the lowpass filtering nature of hu-man visual system results in an illusion of a continuous tone image in a dis-tance. in this paper, we analyze the characteristics of error diffusion system and propose new error diffusion method which conserve grey-level of input image. in the proposed algorithms, we exploits the statistics of error dif-fusion system., as the order of the feedback loop filter increases, the modi-fied input distribution goes to gaussian. based on this phenomena, we deter- mined the optimal quantizer threshold conserving the grey-level of an input image. in addition, to reflect local characteristics, we modulated this threshold by either the local weighted average or the quantized error itself. we combined the proposed algorithm with a color inkjetprinter model which compensates for the distortion caused by the dot-overlap phenomena. in the computer simulation and several subjective testing, we find that the proposed algorithm yields more natural images that are closer to original one than that of the classic error diffusion method.
심병효,구창설,이봉운 한국군사과학기술학회 2000 한국군사과학기술학회지 Vol.3 No.1
Turbo codes are the most exciting and potentially important development in coding theory in recent years. They were introduced in 1993 by Berrou, Glavieux and $Thitimajshima,({(1)}$ and claimed to achieve near Shannon-limit error correction performance with relatively simple component codes and large interleavers. A required Eb/N0 of 0.7㏈ was reported for BER of $10^{-5}$ and code rate of $l/2.^{(1)}$ However, to implement the turbo code system, there are various important details that are necessary to reproduce these results such as AGC gain control, optimal wordlength determination, and metric rescaling. Further, the memory required to implement MAP-based turbo decoder is relatively considerable. In this paper, we confirmed the accuracy of these claims by computer simulation considering these points, and presented a optimal wordlength for Turbo code design. First, based on the analysis and simulation of the turbo decoder, we determined an optimal wordlength of Turbo decoder. Second, we suggested the MAP decoding algorithm based on sliding-window method which reduces the system memory significantly. By computer simulation, we could demonstrate that the suggested fixed-point Turbo decoder operates well with negligible performance loss.
압축센싱 기법을 적용한 선박 수중 방사 소음 신호의 저주파 토널 탐지
김진홍,심병효,안재균,김성일,홍우영,Kim, Jinhong,Shim, Byonghyo,Ahn, Jae-Kyun,Kim, Seongil,Hong, Wooyoung 한국음향학회 2018 韓國音響學會誌 Vol.37 No.1
Compressive sensing allows recovering an original signal which has a small dimension of the signal compared to the dimension of the entire signal in a short period of time through a small number of observations. In this paper, we proposed a method for detecting tonal signal which caused by the machinery component of a vessel such as an engine, gearbox, and support elements. The tonal signal can be modeled as the sparse signal in the frequency domain when it compares to whole spectrum range. Thus, the target tonal signal can be estimated by S-OMP (Simultaneous-Orthogonal Matching Pursuit) which is one of the sparse signal recovery algorithms. In simulation section, we showed that S-OMP algorithm estimated more precise frequencies than the conventional FFT (Fast Fourier Transform) thresholding algorithm in low SNR (Signal to Noise Ratio) region. 압축센싱을 적용하면 전체 신호의 차원 대비 실제 사용하는 신호의 차원이 작은 희소신호의 경우, 적은 수의 관측치를 통하여 빠른 시간 내에 복원이 가능하다. 수중 표적의 기어박스 및 보조 장치 등으로부터 방사되는 신호의 토널 주파수 성분들은 처리하고자 하는 주파수 대역에서 상대적으로 주파수 성분이 적다. 따라서 토널 신호는 주파수 영역 전체 대비 희소신호로 모델링 될 수 있으므로 희소 신호 복원 알고리듬인 S-OMP(Simultaneous-Orthogonal Matching Pursuit)를 이용하여 복원할 수 있다. 본 논문에서는 압축센싱 기법을 이용하여 수중 표적의 방사 소음 신호의 토널 주파수를 검출하는 기법을 제안하고 모의 실험을 통해 성능을 확인한다. 모의실험에서 기존의 FFT(Fast Fourier Transform) 임계치 기법을 이용한 방법에 비해 낮은 SNR(Signal to Noise Ratio)에서도 정확한 토널 성분을 추정 할 수 있음을 확인하였다.
권석법,심병효 대한전자공학회 2012 電子工學會論文誌-SP (Signal processing) Vol.49 No.2
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 []. In addition, we show recovery performance and the reduced number of iteration required to recover the sparse signal. Compressive sensing 분야에서 orthogonal matching pursuit (OMP) 알고리듬은 underdetermined 시스템의 스파스 (sparse)신호를 복구하는 대표적인 greedy 알고리듬으로 많은 관심을 받고 있다. 본 논문에서는 OMP 알고리듬의 반복과정에서 하나이상의 support들을 선택할 수 있도록 하는 OMP 알고리듬의 일반화된 형태의 generalized orthogonal matching pursuit (gOMP)기법을 제안한다. gOMP가 완벽한 신호 복원을 보장하기 위해 restricted isometry property (RIP)를 이용한 충분조건,[]을 제시한다. 실험을 통해 gOMP는 매 반복과정에서 하나 이상의 support들를 선택함으로써 높은 복원 성능과 낮은 복잡도를 가짐을 확인하였다.