• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.121-125
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• 2010

In this paper, we propose the performance improvement technique using convolutional codes for T-DMB watermarking system. By applying the channel coding, the error performance is improved and the capacity of additional data is increased. We certified availability of our proposed technology by using various simulation.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.177-182
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• 2003

Conventional multilayer feedforward artificial neural networks are very effective in dealing with spatial problems. To deal with problems with time dependency, some kinds of memory have to be built in the processing algorithm. In this paper we show how the newly proposed Serial Input Neuron (SIN) convolutional decoders can be derived. As an example, we derive the SIN decoder for rate code with constraint length 3. The SIN is tested in Gaussian channel and the results are compared to the results of the optimal Viterbi decoder. A SIN approach to decode convolutional codes is presented. No supervision is required. The decoder lends itself to pleasing implementations in hardware and processing codes with high speed in a time. However, the speed of the current circuits may set limits to the codes used. With increasing speeds of the circuits in the future, the proposed technique may become a tempting choice for decoding convolutional coding with long constraint lengths.

• 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.

• ETRI Journal
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• v.33 no.3
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• pp.299-309
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• 2011

Energy consumption is a key issue in body sensor networks (BSNs) since energy-constrained sensors monitor the vital signs of human beings in healthcare applications. In this paper, packet size optimization for BSNs has been analyzed to improve the efficiency of energy consumption. Existing studies on packet size optimization in wireless sensor networks cannot be applied to BSNs because the different operational characteristics of nodes and the channel effects of in-body and on-body propagation cannot be captured. In this paper, automatic repeat request (ARQ), forward error correction (FEC) block codes, and FEC convolutional codes have been analyzed regarding their energy efficiency. The hop-length extension technique has been applied to improve this metric with FEC block codes. The theoretical analysis and the numerical evaluations reveal that exploiting FEC schemes improves the energy efficiency, increases the optimal payload packet size, and extends the hop length for all scenarios for in-body and on-body propagation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.1046-1051
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• 1999

It is well known that Parallel Concatenated Convolutional Codes(turbo codes) has a good performance for long block sizes. This thesis has analyzed the performance of turbo code which is based on voice or control frames with short frame sizes in the future mobile communication system. Also, at the similar decoding complexity, the performance of turbo code and convolutional codes in the speech/control frames, and the applicability of this system are considered. As a result, turbo code in short frame sizes present the performance of a BER of $10^{-3}$ or more over 3 iterations in the future mobile communication system. However, at a BER of $10^{-3}$ , if the same complexity is considered, the performance of rate 1/2 turbo code with K = 5 is better than that of convolutional code with K = 9 at low $E_b/N_0$, and the performance of turbo code with K = 3 is superior to that of convolutional code with K = 7. Rate 1/3 turbo code with K = 3 and 5 have similar to performance of rate 1/2 turbo code.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.2063-2076
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• 1996

In this thesis, in order to apply a punctured convolutional codes to the trellis coded modulation(TCM), an efficient punctured trellis coded modulation(PTCM) based on the decomposition of the metric into orthogonal components is presented. Also, a simulation is performed in an additive white Gaussian noise(AWGN) and a rician fading channel modeling the mobile satellite channel. The PTCM combines punctured convolutional coding with MPSK modulation to provide a large coding gain in a power-limited or bandwidth-limited channel. However, in general the use of the punctured convolutional code structure in the decoder results in a performance loss in comparison to trellis codes, due to difficulties in assigning metrics. But, the study shows no loss in performance for punctured trellis coded MPSK in comparison to TCM, and what is more, the punctured convolutional codes results in some savings in the complexity of Viterbi decoders, compared to TCM of the same rate. Also, the results shows that the punctured trellis coded .pi./8 shift 8PSK is an attractive scheme for power-limited and band-limited systems and especially, the Viterbi decoder with first and Lth phase difference metrics improves BER performance by the mobile satellite channel.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1239-1244
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• 2015

In this paper, a new method for finding optimal and short span in Convolutional Self-Doubly Orthogonal(CDO) codes are proposed. This new algorithm based on Parallel Implicitly-Exhaustive search, where we applied dynamic search space reduction methods in order to reduce computational time for finding Optimal Span for R=1/2 rate CDO codes. The simulation results shows that speedup and error correction performance of the new algorithm is better.

• Journal of the Korean Professional Engineers Association
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• v.26 no.3
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• pp.26-33
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• 1993

위성을 이용한 DAMA-SCPC 지구국시스템의 경우 대체적으로 전송경로상에서 발생되는 에러를 제어하는 방법으로 FEC 기법을 채택하고 있다. 본 고에서는 DAMA -SCPC 지구국 시스템의 설계에 적용할 수 있도록 길쌈부호와 Viterbi 복호법, 그리고 (m-1)/m의 부호율을 위한 소기식 길쌈부호에 대해 살펴보고, 상용화 FEC CODEC 제품 중 가격이 비교적 저렴하고 다양한 기능을 제공하는 QUALCOM사의 Q0256 CODEC의 구성 및 제공 기능에 대해 분석한 후, 이 FEC CODEC을 DAMA-SCPC 지구국 시스템의 채널부에 적용시킬 때의 내장 부가 장치와 제공 기능들의 설계 및 이용 방안에 대해 고찰하였다.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.10a
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• pp.79-82
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• 1986

For the purpose of error correcting, a concatenated coding system has been proposed by cascading two codes-(7, 3) Reed-Solomon and (2, 1, 6) convolutional codes. As a result of the result of the computer simulation and the experiment, the (98.21) concatenated code has been show to be able to correct 12 randome error and 16 bust errors. When the channel error is about 1.2x10, this system indicats most efficient.

• 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.