• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.23-33
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• 1996

This paper deals with the design of a recursively-indexed binary code for facsimile soruces and its performance. Sources used here are run-lengths of white pixels form higher-resolution facsimile. The modified huffman code used for G.3 facsimile is chosen for the performance comparison. Experiments confirm the fact that recursive indexing preserves the entropy of a memoryless geometric source: the entropy of recursively-indexed physical surce iwth roughly geometric distributin remains within 2% of the empirical source entropy. The designed recursively-indexed binary codes consist of a code applied to text-type documents and to graphics - type documents is compared iwth that of the modified huffman code. Numerical resutls show that the modified huffman code performs well for text-type documents and not equally well for graphics-tyep documents. On the other hand, recursively-indexed binary codes have shown a better performance for graphics-type documents whose distribution are similar to a geometric distribution. Specifically, the code rates of recursively-indexed binary codes with 60 codewords are from 8% to 20% of the empirical source entropy smaller than that of th emodified huffman code with 91 codewords.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3790-3803
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• 2018

Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.846-852
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• 2006

The ${\kappa}$-error linear complexity is a ky measure of the stability of the sequences used in the areas of communication systems, stream ciphers in cryptology and so on. This paper introduces an efficient algorithm to determine the ${\kappa}$-error linear complexity and the corresponding error vectors of $p^m$-periodic binary sequences, where : is a prime and 2 is a primitive root modulo $p^2$. We also give a new sense about the ${\kappa}$-error linear complexity in viewpoint of coding theory instead of cryptographic results. We present an efficient algorithm for decoding binary cyclic codes of length $p^m$ and derive key properties of the minimum distance of these codes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.11
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• pp.1078-1083
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• 2013

At the ubiquitous age, applications of Wireless Personal Area Network (WPAN) technology using LEDs are in progress. However, visible light communication using LED have weakness, which deteriorates performance of communication. To reduce information losses, which is caused by optical noise, such as incandescent lamps, fluorescent lamps, sunbeam etc., proposed channel coding scheme, double binary turbo codes. In this paper, encoding scheme of the proposed system is described and simulation results are analyzed. We had expected improved performance by using double binary turbo codes. Finally, performances of the proposed system came up to our expectations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.3
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• pp.127-139
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• 2014

In this paper, we present two signal processing techniques for designing binary error correction codes for Multi-Level Cell(MLC) NAND flash memory. MLC NAND flash memory saves the non-binary symbol at each cell and shows asymmetric channel LLR l-density which makes it difficult to design soft-decision binary error correction codes such as LDPC codes and Polar codes. Therefore, we apply density mirroring and EM algorithm for approximating the MLC NAND flash memory channel to the binary-input memoryless channel. The density mirroring processes channel LLRs to satisfy roughly all-zero codeword assumption, and then EM algorithm is applied to l-density after density mirroring for approximating it to mixture of symmetric Gaussian densities. These two signal processing techniques make it possible to use conventional code design algorithms, such as density evolution and EXIT chart, for MLC NAND flash memory channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1176-1178
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• 2016

We propose some binary locally repairable codes with locality 2 uising a parity-check matrix. The minimum distance of the proposed codes is 6. The proposed codes are optimal in the sense of achieving the upper bound of dimension for given length, minimum distance, and locality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.485-499
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• 2021

Although non-binary low-density parity-check (NB-LDPC) codes have better error-correction capability than that of binary LDPC codes, their decoding complexity is significantly higher. Therefore, it is crucial to reduce the decoding complexity of NB-LDPC while maintaining their error-correction capability to adopt them for various applications. The extended min-sum (EMS) algorithm is widely used for decoding NB-LDPC codes, and it reduces the complexity of check node (CN) operations via message truncation. Herein, we propose a low-cost CN processing method to reduce the complexity of CN operations, which take most of the decoding time. Unlike existing studies on low complexity CN operations, the proposed method employs quick selection algorithm, thereby reducing the hardware complexity and CN operation time. The experimental results show that the proposed selection-based CN operation is more than three times faster and achieves better error-correction performance than the conventional EMS algorithm.

• Journal of IKEEE
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• v.22 no.3
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• pp.850-853
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• 2018

In this paper, we propose a decoding method using a balanced binary tree and a canonical Huffman tree for efficient decoding of Huffman codes. The balanced binary tree scheme reduces the number of searches by lowering the height of the tree and binary search. However, constructing a tree based on the value of the code instead of frequency of symbol is a drawback of the balanced binary tree. In order to overcome these drawbacks, a balanced binary tree is reconstructed according to the occurrence probability of symbols at each level of the tree and binary search is performed for each level. We minimize the number of searches using a canonical Huffman tree to find level of code to avoid searching sequentially from the top level to bottom level.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.109-117
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• 2013

Polar codes are the first provable error correcting code achieving the symmetric channel capacity in a wide case of binary input discrete memoryless channel(BI-DMC). However, finite length polar codes have an error floor problem with successive-cancellation list(SCL) decoder. From previous works, we can solve this problem by concatenating CRC(Cyclic Redundancy Check) codes. In this paper we propose to make polar codes having extended-minimum distance from original polar codes without outer codes using correlation with generate matrix of polar codes and that of RM(Reed-Muller) codes. And we compare performance of proposed polar codes with that of polar codes concatenating CRC codes.

• 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).