• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.10
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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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• v.12 no.8
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.2
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1143-1149
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• 2006

In this paper, the modified iterative decoding algorithm[8] by partitioning check nodes is applied to low-density parity-check(LDPC) codes in IEEE 802.16e standards, which gives us the improvement for convergence speed of decoding. Also, the new method of check node partitioning which is suitable for decoding of the LDPC codes in IEEE 802.16e system is proposed. The improvement of convergence speed in decoding reduces the number of iterations and thus the computational complexity of the decoder. The decoding method by partitioning check nodes can be applied to the LDPC codes whose decoder cannot be implemented in the fully parallel processing as an efficient sequential processing method. The modified iterative decoding method of LDPC codes using the proposed check node partitioning method can be used to implement the practical decoder in the wireless communication systems.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.69-80
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• 2021

Neural machine translation using deep neural network has emerged as a mainstream research, and an abundance of investment and studies on model structure and parallel language pair have been actively undertaken for the best performance. However, most recent neural machine translation studies pass along decoding strategy to future work, and have insufficient a variety of experiments and specific analysis on it for generating language to maximize quality in the decoding process. In machine translation, decoding strategies optimize navigation paths in the process of generating translation sentences and performance improvement is possible without model modifications or data expansion. This paper compares and analyzes the significant effects of the decoding strategy from classical greedy decoding to the latest Dynamic Beam Allocation (DBA) in neural machine translation using a sequence to sequence model.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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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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• v.9 no.6
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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 = $10^{-5}$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.10
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• pp.619-621
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• 2014

In this letter, an MMSE based continuous turbo equalizer is proposed for MIMO-HARQ systems. In the proposed scheme, the soft information from the reception process for the previous transmission is reutilized at the initialization of the reception process for the next transmission to enhance the decoding convergence speed. Simulation results verify that the proposed scheme achieves an improved BLER with a significantly accelerated decoding convergence speed.

• Journal of the Korea Convergence Society
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• v.4 no.4
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• pp.21-29
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• 2013

Two-dimensional QR Code has improved greatly the limits on the capacity, size, direction of the one-dimensional bar code. And it has the capacity of compressing and storing the massive amount of data and is widely used in many applications. Recently, the two-dimensional QR Code has been spread rapidly because of introducing the smart phones and increasing the amount of using them. However, there is little documentations about decoding the QR Code in which can store the large amount of information. In this paper, therefore, we present specific processing procedures and algorithms on decoding the two-dimensional QR Code and then make us understand their decoding process by explaining some examples.