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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.
문지훈,심병효 한국통신학회 2022 韓國通信學會論文誌 Vol.47 No.10
In this paper, we propose a deep reinforcement learning (DRL)-based method to satisfy diverse requirements in vehicular communications. Using the channel as the input, the actor-critic algorithm outputs the resource allocation maximizing the network sum rate while ensuring the requirements. 본 논문에서는 차량 간 통신에서 다양한 요구 조건을 만족하기 위해 심층강화학습을 사용하는 방안을제시한다. 심층강화학습 중 actor-critic 알고리즘을 활용해 주변 채널 상황을 입력으로 받아 자원 할당을출력해 차량 별 요구 조건을 만족하면서 네트워크 데이터 전송률 합을 최대화한다.
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.