• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1513-1526
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• 2009

The SVC (Scalable Video Coding) scheme can be effectively used for reducing the redundancy and for improving the coding efficiency but, it requires very high computational complexities. In order to accelerate the successful standardization and commercialization of the Advanced Terrestrial-DMB service, it is necessary to overcome this problem. For this aim, in this paper, we propose an efficient aggregated encoder control algorithm, which shows better performances than the conventional control scheme. Computer simulation result shows that the proposed scheme performs about up to 0.3dB better than those of the conventional scheme. Additionally, based on this control scheme, we propose a fast mode decision method by constraining the redundant coding modes based on the statistical properties of the quantization parameter in the spatial scalable encoder. Through computer simulations, it is shown that the proposed control schemes reduce the heavy computational burden up to 12% compared to the conventional scheme, while keeping the objective visual qualify very high.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.3
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• pp.246-252
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• 2018

Recent studies have been received much attention on underwater laser communication, which is capable of high data rate. However, in underwater laser communication, distortions caused by absorption and scattering induced performance degradation. A typical way to improve performance is to apply channel coding technique. In the beginning of studies, simple methods such as RS and BCH coding techniques were applied. However, due to distance expansion and performance improvement, channel coding methods with low error probability such as LDPC coded method were applied. In this paper, we analyzed the performance according to the size of the code word N, the distance between the transceivers and the size of the M of the M-ary PPM modulation scheme. Simulation results show that parameter M of M-ary PPM is most effect on performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.50-57
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• 2009

This paper presents a new model-based macroblock layer rate control algorithm for low bit rate video coding which generates output bits corresponding to a target bit budget. The H.264 standard uses various coding modes and optimization methods to improve the compression performance, which makes it difficult to control the generated traffic accurately in low bit rate environments. In the proposed scheme, we first estimate MAD values of macroblocks in a frame and define a target remaining bits using the estimated MAD values before encoding each macroblock. If a difference between the target value and the actual value is greater than a threshold value, the quantization parameter is adjusted to decrease the difference. It is shown by experimental results that the new algorithm can obtain more than 66% decrease of the difference between the target bits and the resulting bits for a frame with the PSNR performance better than that of the existing rate control algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2043-2052
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• 1997

The object-oriented coding technique which is one of the coding methods in very low bit rate environment is suitable for videophone image sequence. The selection of source model affect image analysis. In this paper, an image analysis method for the object-oriented coding is presented. The process is composed of changed region detection andmotion estimateion. First, we use the standard deviation of frame difference as thrreshold to extract themoving area. If thesum of gray values in mask is greater than the threshold, the center pixel of the mask is regarded as moving region. After moving is detected in changed region by edge operator, observation point is determined from moving region. The motion is estimated by 6-parameter mapping method with determined observation point. The experimantal resutls show that the proposed method can significantly improve the image quality.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.277-280
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• 2001

The preprocessing is very important course in speech signal processing. It influence the compression-rate in speech coding and the recognition-rate in speech recognition etc. In this paper, we propose that minimizing window-influence method with pitch period and start points. The proposed method is available for voiced detection and word labeling.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.49-53
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• 1992

In many applications such as speech analysis, speech coding, speech recognition, etc., the voiced-unvoiced decision should be performed correctly for efficient processing. One of the parameters which are used for voice-unvoiced decision is zero-crossing. But the information of higher formants have not represented as the zero-crossing rate for higher formants of speech signals.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.120-123
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• 1997

This paper presents models of fuzzy inference systems that can be built from a set of input-output training data pairs through hybrid structure-parameter learning. Fuzzy inference systems has the difficulty of parameter learning. Here we develop a coding format to determine a fuzzy neural network(FNN) model by chromosome in a genetic algorithm(GA) and present systematic approach to identify the parameters and structure of FNN. The proposed FNN can automatically identify the fuzzy rules and tune the membership functions by modifying the connection weights of the networks using the GA and the back-propagation learning algorithm. In order to show effectiveness of it we simulate and compare with conventional methods.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.96-108
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• 1996

In this paper, we propose an object-oriented coding method in low bit-rate channels using block-based motion vectors and residual image compensation. First, we use a 2-stage algorithm for estimating motion parameters. In the first stage, coarse motion parameters are estimated by fitting block-based motion vectors and in the second stage, the estimated motion parametes are refined by the gradient method using an image reconstructed by motion vectors detected in the first stage. Local error of a 6-parameter model is compensted by blockwise motion parameter correction using residual image. Finally, model failure (MF) region is reconstructed by a fractal mapping method. Computer simulation resutls show that the proposed method gives better performance than the conventional ones in terms of th epeak signal to noise ratio (PSNR) and compression ratio (CR).

• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.