• 한국통신학회논문지
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• 제39A권10호
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• pp.585-592
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• 2014

It is well known that serial belief propagation (BP) decoding for low-density parity-check (LDPC) codes achieves faster convergence without any increase of decoding complexity per iteration and bit error rate (BER) performance loss than standard parallel BP (PBP) decoding. Serial BP (SBP) decoding, such as horizontal SBP (H-SBP) decoding or vertical SBP (V-SBP) decoding, updates check nodes or variable nodes faster than standard PBP decoding within a single iteration. In this paper, we propose combined horizontal-vertical SBP (CHV-SBP) decoding. By the same reasoning, CHV-SBP decoding updates check nodes or variable nodes faster than SBP decoding within a serialized step in an iteration. CHV-SBP decoding achieves faster convergence than H-SBP or V-SBP decoding. We compare these decoding schemes in details. We also show in simulations that the convergence rate, in iterations, for CHV-SBP decoding is about $\frac{1}{6}$ of that for standard PBP decoding, while the convergence rate for SBP decoding is about $\frac{1}{2}$ of that for standard PBP decoding. In simulations, we use recently proposed generalized LDPC (GLDPC) codes with binary cyclic codes (BCC).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3749-3768
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• 2018

As one of the most potential types of low-density parity-check (LDPC) codes, CPM-QC-LDPC code has considerable advantages but there still exist some limitations in practical application, for example, the existing decoding algorithm has a low convergence rate and a high decoding complexity. According to the structural property of this code, we propose a new method based on a CPM-RID decoding algorithm that decodes block-by-block with weights, which are obtained by neural network training. From the simulation results, we can conclude that our proposed method not only improves the bit error rate and frame error rate performance but also increases the convergence rate, when compared with the original CPM-RID decoding algorithm and scaled MSA algorithm.

• 한국통신학회논문지
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• 제22권2호
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• pp.325-333
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• 1997

In fractral decoding procedure, the reconstructed image is obtained by iteratively applying the contractive transform to an arbitrary initial image. But this method is not suitable for the fast decoding because convergence speed depends on the selection of initial image. Therefore, the initial image to achieve fast decoding should be selected. In this paper, we propose an initial image estimation that can be applied to various decoding methods. The initial image similar to the original image is estimated by using only the compressed data so that the proposed method does not affect the compression ratio. From the simulation, the PSNR of the proposed initial image is 6dB higher han that of ones iterated output image of conventional decoding with Babaraimage. Computations in addition and multiplication are reduced about 96%. On the other hands, if we apply the proposed initial image to other decoding algorithms, the faster convergence speed is expected.

• 한국통신학회논문지
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• 제31권12C호
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• pp.1143-1149
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• 2006

본 논문에서는 체크 노드 분할을 이용한 변형된 반복 복호 방법 [8]을 IEEE 802.16e 표준에서 제시된 low-density parity-check(LDPC) 부호에 적용하여 복호의 수렴 속도 개선을 확인한다 또한 IEEE 802.16e에서 제시된 LDPC 부호에 가장 적합한 체크 노드 분할 방법을 제안한다. 수렴 속도 개선은 반복 횟수를 줄일 수 있다는 의미에서 계산 복잡도를 감소시킬 수 있다. 이러한 체크 노드 분할을 이용한 복호 방법은 복호기의 하드웨어 구현이 병렬 처리 방식으로 구현되기 어려운 시스템에서 효과적인 직렬 처리 방식으로 적용될 수 있다. 제시된 LDPC 부호의 변형된 반복 복호 방법은 무선 통신 시스템 환경의 실제 복호기를 구현하는데 사용될 수 있다.

• 한국융합학회논문지
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• 제12권11호
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• pp.69-80
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• 2021

딥러닝 모델을 활용한 인공신경망 기계번역 (Neural machine translation)이 주류 분야로 떠오르면서 최고의 성능을 위해 모델과 데이터 언어 쌍에 대한 많은 투자와 연구가 활발하게 진행되고 있다. 그러나, 최근 대부분의 인공신경망 기계번역 연구들은 번역 문장의 품질을 극대화하는 자연어 생성을 위한 디코딩 전략 (Decoding strategy)에 대해서는 미래 연구 과제로 남겨둔 채 다양한 실험과 구체적인 분석이 부족한 상황이다. 기계번역에서 디코딩 전략은 번역 문장을 생성하는 과정에서 탐색 경로를 최적화 하고, 모델 변경 및 데이터 확장 없이도 성능 개선이 가능하다. 본 논문은 시퀀스 투 시퀀스 (Sequence to Sequence) 모델을 활용한 신경망 기반의 기계번역에서 고전적인 그리디 디코딩 (Greedy decoding)부터 최신의 방법론인 Dynamic Beam Allocation (DBA)까지 비교 분석하여 디코딩 전략의 효과와 그 의의를 밝힌다.

• 전자공학회논문지S
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• 제34S권8호
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• 한국통신학회논문지
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• 제23권9A호
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• pp.2355-2364
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• 1998

In conventional fractal decoding procedure, the reconstructed image is obtained by a rpredefined number of iterations starting with an arbitrary initial image. Its convergence speed depends on the selection of the initial image. It should be solved to get high speed convergence. In this paper, we theoretically reveal that conventional method is approximately decomposed into the decoding of the DC and AC components. Based on this fact, we proposed a novel fast fractal decoding algorithm made up of two steps. The averaged-image considered as an optimal initial image is estimated in the first step. In the second step, the reconstructe dimag eis genrated from the output image obtained in the first step. From the simulations, it is shown that the output image of the first step approximately converges to the averaged-image with only 15% calculations for one iteration of conventional method. And the proposed method is faster than various decoding mehtods and evenly equal to conventioanl decoding with the averaged-image. In addition, the proposed method can be applied to the compressed data resulted from the various encoding methods because it does not impose any constraints in the encoding procedure to get high decoding speed.

• Journal of information and communication convergence engineering
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• 제9권6호
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• pp.657-660
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• 2011

Differential detection algorithm for DBO-CSS based on maximum signal energy detection (MSED) using viterbi algorithm is proposed. In order to mitigate SNR degradation caused by differential decoding, a modified viterbi algorithm with so called correlation metric (CM) in every state is proposed. It is shown that the performance gain of the proposed algorithm when compared with that of the conventional differential detection with the block decoding algorithm is about 2.5dB at BER = $10^{-5}$.

• 한국통신학회논문지
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• 제39A권10호
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• pp.619-621
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• 2014

본 논문은 MIMO-HARQ 시스템을 위한 MMSE 기반 연속 터보 등화기를 제안한다. 제안 기법은 이전 전송의 수신 과정 중 생성된 연판정 정보를 재전송의 수신 과정 중 초기화 단계에서 재활용하여 복호수렴 속도의 개선을 도모한다. 모의실험을 통해 제안기법이 기존 기법 대비 향상된 블록 오율을 달성함과 동시에 복호 수렴 속도를 크게 개선함을 확인하였다.

• 한국융합학회논문지
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• 제4권4호
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• pp.21-29
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• 2013

2차원 QR Code는 1차원 바코드의 용량, 크기, 방향에 대한 한계를 개선하였으며, 방대한량의 데이터를 압축하여 저장할 수 있는 능력을 갖추고 많은 응용분야에서 사용되고 있다. 최근에는 QR Code를 인식할 수 있는 스마트 폰의 도입과 사용의 증대로 QR Code의 도입이 급속도로 확산되었다. 하지만 다양한 정보를 저장할 수 있는 QR Code의 디코딩 기술에 대한 구체적인 문서화가 없는 상태이다. 따라서 본 논문에서는 QR code의 인코딩에 따른 디코딩 과정에 대해 구체적인 처리 절차와 알고리즘을 제시하고 예를 통해 디코딩 과정을 상세히 이해시키는데 연구목적이 있다.