• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.143-149
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• 2006

Turbo code, a kind of error correction coding technique, has been used in the field of digital mobile communication system. As the number of iterations increases, it can achieves remarkable BER performance over AWGN channel environment. However, if the number of iterations is increased in the several channel environments, any further iteration results in very little improvement, and requires much delay and computation in proportion to the number of iterations. To solve this problems, it is necessary to device an efficient criterion to stop the iteration process and prevent unnecessary delay and computation. In this paper, it proposes an efficient and simple criterion for stopping the iteration process in turbo decoding. By using sign changed ratio of extrinsic information values in turbo decoder, the proposed algorithm can largely reduce the average number of iterations without BER performance degradation. As a result of simulations, the average number of iterations is reduced by about $12.48%{\sim}22.22%$ compared to CE algorithm and about $20.43%{\sim}54.02%$ compared to SDR algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.972-983
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• 1996

This paper proposes a new technique for frequency offset correction for OFDM systems on a frequency selective fading channel. Frequency offset in OFDM introduces interchannel interference among the multiple subcarriers of OFDM signal. To compensate the interference, this paper describes an algorithm with two stages:acquisition and tracking. At both stages, the proposed algorithm oversamples the received OFDM signal to obtain a couple of demodulated symbol sets. At acquisition stage the frequency offset is reduced to half or less of the intercarrier spacings by matching the sign pattern of each element of the sets. Next, at tracking stage the frequency offset is corrected with a frequency detector which is controlled by the correlation of the two sets. It is shown that the proposed algorithm can correct the frequency offset in the event of uncertainty in the initial offset that exceeds one half of the intercarrier spacing. In addition, the proposed algorithm is robust to transmitted symbols and channel characteristics by using oversampled symbol sets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2148-2161
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• 2019

In this paper, we present a real-time cattle action recognition algorithm to detect the estrus phase of cattle from a live video stream. In order to classify cattle movement, specifically, to detect the mounting action, the most observable sign of the estrus phase, a simple yet effective feature description exploiting motion history images (MHI) is designed. By learning the proposed features using the support vector machine framework, various representative cattle actions, such as mounting, walking, tail wagging, and foot stamping, can be recognized robustly in complex scenes. Thanks to low complexity of the proposed action recognition algorithm, multiple cattle in three enclosures can be monitored simultaneously using a single fisheye camera. Through extensive experiments with real video streams, we confirmed that the proposed algorithm outperforms a conventional human action recognition algorithm by 18% in terms of recognition accuracy even with much smaller dimensional feature description.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2465-2473
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• 2011

This paper describes a circuit-level optimization of DFU(decoding function unit) for LDPC decoder which is used in wireless communication systems including WiMAX and WLAN. A new design of DFU based on sign-magnitude arithmetic instead of two's complement arithmetic is proposed, resulting in 18% reduction of gate count for 96 DFUs array used in mobile WiMAX LDPC decoder. A multi-mode LDPC decoder for mobile WiMAX standard is designed using the proposed DFU. The LDPC decoder synthesized using a 0.18-${\mu}m$ CMOS cell library with 50 MHz clock has 268,870 gates and 71,424 bits RAM, and it is verified by FPGA implementation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1319-1323
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• 2004

In this paper, a problem of Thai sign language recognition using a neural network is considered. The paper addresses the problem in classifying certain signs conveying quantitative meaning, e.g., large or small. By treating those signs corresponding to different quantities as derived from different classes, the recognition error rate of the standard multi-layer Perceptron increases if the precision in recognizing different quantities is increased. This is due the fact that, to increase the quantitative recognition precision of those signs, the number of (increasingly similar) classes must also be increased. This leads to an increase in false classification. The problem is due to misinterpreting the amount of quantity the quantitative signs convey. In this paper, instead of treating those signs conveying quantitative attribute of the same quantity type (such as 'size' or 'amount') as derived from different classes, here they are considered instances of the same class. Those signs of the same quantity type are then further divided into different subclasses according to the level of quantity each sign is associated with. By using this two-level classification, false classification among main gesture classes is made independent to the level of precision needed in recognizing different quantitative levels. Moreover, precision of quantitative level classification can be made higher during the recognition phase, as compared to that used in the training phase. A standard multi-layer Perceptron with a back propagation learning algorithm was adapted in the study to implement this two-level classification of quantitative gesture signs. Experimental results obtained using an electronic glove measurement of hand postures are included.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.9
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• pp.65-70
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• 2008

In FIR filter design, multipliers occupy most of the area. To efficiently reduce the area occupied by multipliers, Common Subexpression Elimination (CSE) algorithm can be used instead of separate multipliers. However, the filter computation time can be increased due to the long carry propagation in CSE circuits. More specifically, when the difference of weights between the two inputs to an adder in CSE circuits is large, long carry propagation time is required due to large sign extension. In this paper, we propose a sign-extension reduction method in common subexpression elimination circuit. By Synopsys simulation using Samsung 0.35um library, it is shown that the proposed method leads to 17%, 31% and 12% reduction in the area, time delay and power consumption, respectively, compared with conventional method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.29-37
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• 2009

This paper describes a vision-based and real-time system for detecting road signs from within a moving vehicle. The proposed system has the standard architecture with adaboost algorithm to detect road signs in real time. And it uses the value of vortical plane in the process of extracting candidate areas in view of fact that there are vertically most of signs on roads. Although being useful for detecting objects in real time, the conventional adaboost algorithm deteriorates the performance of detection rate in complex circumstance by reason of using only integral images as features. To overcome this problem, this paper proposes the method that improves the reliability of candidates as using the value of vertical plane for extracting candidate area and improves the performance of the detection rate as using integral images to which we add the kind of feature prototype. The experiments of this paper show that the detection rate of the proposed method has higher than that of the conventional adaboost algorithm under the real complex circumstance of roads.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.11
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• pp.75-83
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• 1999

We propose a PfSGA(parameter-free species genetic algorithm) to learn the topological structure of MLP classifiers being adequate to given applications. The PfSGA is a combinational method of SGA(species genetic algorithm) and PfGA(parameter-free genetic algorithm). In SGA, we divide the total search space into several subspaces(species) according to the number of hidden units, and reduce the unnecessary search by eliminating the low promising species from the evolutionary process. However the performances of SGA classifiers are readily affected by the values of parameters such as mutation ratio and crossover ratio. In this paper, therefore, we combine SGA with PfGA, for which it is not necessary to determine the learning parameters. Experimental results on benchmark data and sign language words show that PfSGA can reduce the learning time of SGA and is not affected by the selection parameter values on structural learning. The results also show that PfSGA is more efficient than the exisiting methods in the aspect of misclassification ratio, learning rate, and complexity of MLP structure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.55-60
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• 2021

This paper relates with the performance evaluation of QE-MMA (Quantized Error-MMA) adaptive equalization algorithm based on the stepsize and quantizer bit number in order to reduce the intersymbol interference due to nonlinear distortion occurred in the time dispersive channel. The QE-MMA was proposed using the power-of-two arithmetic for the H/W implementation easiness substitutes the multiplication and addition into the shift and addition in the tap coefficient updates process that modifies the SE-MMA which use the high-order statistics of transmitted signal and sign of error signal. But it has different adaptive equalization performance by the step size and quantizer bit number for obtain the sign of error in the generation of error signal in QE-MMA, and it was confirmed by computer simulation. As a simulation, it was confirmed that the convergence speed for reaching steady state depend on stepsize and the residual quantities after steady state depend on the quantizer bit number in the QE-MMA adaptive equalization algorithm performance.