• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.296-306
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• 2003

In this paper, algorithm for non-iterative decoding method is proposed and fractal image decoder based on non-iterative fractal decoding algorithm used general purpose digital signal processors is designed and implemented. The algorithm is showed that the attractor image can be obtained analytically whe n the image is encoded using the fractal algorithm proposed by Monro and Dudbridge, in which the corresponding domain block for a range block is fifed. Using the analytical formulas, we can obtain the attractor image without iteration procedure. And we get general formulas of obtained analytical formulas. Computer simulation results for various test images show that we can increase the image decoding speed by more than five times when we use the analytical formulas compared to the previous iteration methods. The fractal image decoder contains two ADSP2181's and perform image decoding by three stage pipeline structure. The performance tests of the implemented decoder is elapsed 31.2ms/frame decoding speed for QCIF data when all the frames are decoded. The results enable us to process the real-time fractal decoding over 30 frames/sec.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.961-967
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• 2014

Raptor codes are a class of rateless codes originally designed for binary erasure channels. This paper presents a compact set of mathematical expressions for iterative soft decoding of raptor codes. In addition, an early termination scheme is employed, and it is embedded in a single algorithm with the formula. In the proposed algorithm, the performance is enhanced by adopting iterative decoding, both in each inner and outer code and in the concatenated code itself between the inner and outer codes. At the same time, the complexity is reduced by applying an efficient early termination scheme. Simulation results show that our proposed method can achieve better performance with reduced decoding complexity compared to the conventional schemes.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.40-49
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• 2016

In this paper, we present a symbol-level iterative source-channel decoding (ISCD) algorithm for reliable transmission of variable-length codes (VLCs). Firstly, an improved source a posteriori probability (APP) decoding approach is proposed for packetized variable-length encoded Markov sources. Also proposed is a recursive implementation based on a three-dimensional joint trellis for symbol decoding of binary convolutional codes. APP channel decoding on this joint trellis is realized by modification of the Bahl-Cocke-Jelinek-Raviv algorithm and adaptation to the non-stationary VLC trellis. Simulation results indicate that the proposed ISCD scheme allows to exchange between its constituent decoders the symbol-level extrinsic information and achieves high robustness against channel noises.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8A
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• pp.1156-1162
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• 1999

In this paper, the problem of decoding transmitted data sequence with diversity reception in the presence of nondelective fading is studied. The expection maximizaton (EM) algorithm is employed to derive an interactive algorithm. The algorithm performs block-by-block coherent decoding with the aid of pilot symbols. It is shown that the complexity of the algorithm grows linearly as a function of sequence length. The performance of the algorithm is shown to better than that of the conventional pilot symbol aided (PSI) algorithm. Simulation results are presented to assess the performance of the algorithm and the results are compared with that of the conventional PSI alforithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1387-1394
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• 2004

Turbo code, a kind of error correction coding technique, has been used in the field of digital mobile communication systems. And it is well known about the fact that turbo code has better the BER performance as the number of decoding iterations increases in the AWGN channel environment. However, as the number of decoding iterations is increased under the several channel environments, any further iteration results in very little improvement, and it requires much delay, computation and power consumption in proportion to the number of decoding iterations. In this paper, it proposes the efficient iterative decoding stop criterion algorithm which can largely reduce the average number of decoding iterations of turbo code. Through simulations, it is verifying that the proposed algorithm can efficiently stop the iterative decoding by using the variance value of error probability for the soft output value, and can largely reduce the average number of decoding iterations without BER performance degradation. As a result of simulation, the average number of decoding iterations for the proposed algorithm is reduced by about 2.25% ~14.31％ and 3.79％ ~14.38% respectively compared to conventional schemes, and power consumption is saved in proportion to the number of decoding iterations.

• MALSORI
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• no.50
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• pp.51-69
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• 2004

In this paper, we present a one-pass semi-dynamic network decoding framework that inherits both advantages of fast decoding speed from static network decoders and memory efficiency from dynamic network decoders. Our method is based on the novel language model network representation that is essentially of finite state machine (FSM). The static network derived from the language model network [1][2] is partitioned into smaller subnetworks which are static by nature or self-structured. The whole network is dynamically managed so that those subnetworks required for decoding are cached in memory. The network is near-minimized by applying the tail-sharing algorithm. Our decoder is evaluated on the 25k-word Korean broadcast news transcription task. In case of the search network itself, the network is reduced by 73.4% from the tail-sharing algorithm. Compared with the equivalent static network decoder, the semi-dynamic network decoder has increased at most 6% in decoding time while it can be flexibly adapted to the various memory configurations, giving the minimal usage of 37.6% of the complete network size.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.328-332
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• 2003

Since Jacquine introduced the image coding algorithm using fractal theory, many fractal image compression algorithms providing good quality at low bit rate have been proposed by Fisher and Beaumount et al.. But a problem of the previous implementations is that the decoding rests on an iterative procedure whose complexity is image -dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and a input image to be encoded. As the decoding process can be completed with received fractal coefficients and predefined initial image without repeated iterations, the decoding time could be remarkably reduced.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.434-440
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• 2003

Since Jacquine introduced the image coding algorithm using fractal theory, many fractal image compression algorithms providing good quality at low bit rate have been proposed by Fisher and Beaumount et al.. But a problem of the previous implementations is that the decoding rests on an iterative procedure whose complexity is image-dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and an input image to be encoded. As the decoding process can be completed with received fractal coefficients and predefined initial image without repeated iterations, the decoding time could be remarkably reduced.

• ETRI Journal
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• v.25 no.1
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• pp.1-8
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• 2003

This paper introduces an efficient iterative decoding method for high-dimensional block turbo codes. To improve the decoding performance, we modified the soft decision Viterbi decoding algorithm, which is a trellis-based method. The iteration number can be significantly reduced in the soft output decoding process by applying multiple usage of extrinsic reliability information from all available axes and appropriately normalizing them. Our simulation results reveal that the proposed decoding process needs only about 30% of the iterations required to obtain the same performance with the conventional method at a bit error rate range of $10^{-5}\;to\;10^{-6}$.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.7
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• pp.705-710
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• 2011

In this paper, we proposed the low computational complexity soft-decision e-BCH decoding algorithm based on the Chase algorithm. In order to make the test patterns, it is necessary to re-order the least reliable received symbols. In the process of ordering and finding optimal decoding symbols, high computational complexity is required. Therefore, this paper proposes the method of low computational complexity algorithm for soft-decision e-BCH decoding process.