• 음성과학
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• 제11권4호
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• pp.89-97
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• 2004

In this paper, an improved network echo canceller is proposed. The proposed echo canceller is based on the LTJ(lattice transversal joint) adaptive filter which uses informations from the speech decoder. In the proposed implementation method of the network echo canceller, the filer coefficients of the transversal filter part in the LTJ adaptive filter is updated every other sample instead of every sample. So its complexity can be lower than that of the transversal filter. And the echo cancellation rate can be improved by residual echo cancellation using the lattice predictor whose order is less than 10. Computational complexity of the proposed echo canceller is lower than that of the transversal filter but the convergence speed is faster than that of the transversal filter. The performance improvement of the proposed echo canceller was verified by the experiments using the real speech signal and speech coder.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.261-264
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• 1993

This paper proposes an adaptive generalized predictive control with feedforward algorithm for steam generator level control in nuclear power plant. The proposed algorithm is shown that the parameters of N-step ahead predictors can be obtained using the parameters of one-step ahead predictor which is derived from plant model with feedforward. Using this property the proposed scheme is an adaptive algorithm which consists of GPC method and the recursive least squares algorithm for identifying the parameters of one-step ahead predictor. Also, computer simulations are performed to evaluate the performance of proposed algorithm using a mathematical model of PWR steam generator Simulation results show good performances for load variation. And the proposed algorithm shows better responses than PI controller does.

• 전기학회논문지
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• 제63권12호
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• pp.1704-1709
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• 2014

In order to increase the performance of multi-core system processor architectures, the multi-thread branch predictor which speculatively fetches and allocates threads to each core should be highly accurate. In this paper, the perceptron based multi-thread branch predictor is proposed for the multi-core processor architectures. Using SPEC 2000 benchmarks as input, the trace-driven simulation has been performed for the 2 to 16-core architectures employing perceptron multi-thread branch predictor extensively. Its performance is compared with the architecture which utilizes the two-level adaptive multi-thread branch predictor.

• Journal of electromagnetic engineering and science
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• 제16권2호
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• pp.80-86
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• 2016

This paper proposes the algorithm for forward link adaptive coding and modulation (ACM) and the detailed design for a satellite communication system to improve network reliability and system throughput. In the ACM scheme, the coding and modulation schemes are changed by as much as the channel can provide depending on the quality of the communication link. To implement the forward link ACM system in the Ka-band, channel prediction and modulation/coding decision methods are proposed and simulated. The parameters of the adaptive filter predictor based on the least mean square are optimized, the minimum mean square error of the channel predictor is 0.0608 when step size and the number of filter tap are 0.0001 and 4, respectively. A test-bed is set up to verify the forward link ACM system, and a test is performed using a Ka-band satellite (i.e., Communication, Ocean, and Meteorological Satellite [COMS]). This test verifies that the ACM scheme can increase the system throughput.

• 한국대기환경학회지
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• 제2권3호
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• pp.52-56
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• 1986

In this paper a adaptive LMS(least mean-square) lattice predictor, which is composed of the adaptive lattice algorithm and LMS algorithm by Widrow-Hopf, is used to predict the future air pollution of the extraordinary levels in the environmental system. This prediction algorithm is applied to the one-step forward prediction of atmospheric CO concentration by using real observed data. Computer simulation proves that the power in the forward error sequences decreases as the number of stages in the lattice is increased.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.941-943
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• 1995

The convergence of adaptive algorithm depends mainly on the proper choice of the design factor called the covergence factor. In the paper, an optimal convergence factor involved in TRLMS algorithm, which is used to predict the coefficients of the ARMA predictor in ADPCM is presented. It is shown that such an optimal value can be generated by system signals such that the adaptive filter becomes self optimizing in terms of the convergence factor. This algorithm is applied to real image.

• 디지털산업정보학회논문지
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• 제5권3호
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• pp.141-145
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• 2009

In this paper, we propose an efficient lossless compression algorithm using spatial and temporal information. The proposed method obtains higher lossless compression of images than other lossless compression techniques. It is divided into two parts, a motion adaptation based predictor part and a residual error coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors. The predictor decides the proper selection of the spatial and temporal prediction values according to each past prediction error. The reduced error is coded by existing context coding method. Experimental results show that the proposed algorithm has better performance than those of existing context modeling methods.

• 한국통신학회논문지
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• 제31권12A호
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• pp.1182-1188
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• 2006

적응 변조 OFDM(Orthogonal Frequency Division Multiplexing) 전송 기법은 각 부반송파의 채널 상태에 따라 변조방식을 적절히 변화시켜 무선 채널의 다중 경로 페이딩에 의해 의한 영향을 최소화하여 시스템의 성능을 증가시키는 방식이다. 시스템이 적응적으로 전송하기위해서는 단말기에서 각 부반송파(subcarrier)별 채널 상태 정보 (Channel State Information : CSI)를 되먹임 채널을 통해 실시간으로 기지국으로 전송해 주어야한다. 하지만, 단말기에서 데이터를 처리할 때 걸리는 시간과, 단말기에서 기지국으로 CSI를 되먹임(feedback) 할 때 걸리는 시간으로 인한 되먹임 지연(feedback delay) d가 발생하게 된다. 이 되먹임 지연은 CSI 정보의 불일치를 발생시켜 적응 OFDM 시스템의 성능저하를 일으킨다. 본 논문에서는 CSI의 되먹임 지연 $d(\geq2)$를 적절히 보상하는 주파수 축 멀티 스탭 채널 예측기를 제안하고 이를 적응 전송 OFDM 시스템에 적용하고 모의실험을 통하여 기존의 OFDM 시스템, 기존의 채널 예측방식과의 성능을 MSE(mean square error), 비트오율(bit error rate : BER) 및 채널용량을 바탕으로 비교한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.2018-2043
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• 2022

Nowadays, COVID-19 infections are influencing our daily lives which have spread globally. The major symptoms' of COVID-19 are dry cough, sore throat, and fever which in turn to critical complications like multi organs failure, acute respiratory distress syndrome, etc. Therefore, to hinder the spread of COVID-19, a Computerized Doughty Predictor Framework (CDPF) is developed to yield benefits in monitoring the progression of disease from Chest CT images which will reduce the mortality rates significantly. The proposed framework CDPF employs Convolutional Neural Network (CNN) as a feature extractor to extract the features from CT images. Subsequently, the extracted features are fed into the Adaptive Dragonfly Algorithm (ADA) to extract the most significant features which will smoothly drive the diagnosing of the COVID and Non-COVID cases with the support of Doughty Learners (DL). This paper uses the publicly available SARS-CoV-2 and Github COVID CT dataset which contains 2482 and 812 CT images with two class labels COVID⁺ and COVI^-. The performance of CDPF is evaluated against existing state of art approaches, which shows the superiority of CDPF with the diagnosis accuracy of about 99.76%.

• 한국음향학회지
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• 제34권5호
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• pp.403-409
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• 2015

본 논문에서는 G.711 패킷 손실 은닉 알고리즘의 성능향상을 위해 적응적 신호 크기 예측을 사용하는 패킷 손실 알고리즘을 제안한다. 기존의 방법은 연속 손실이 발생하였을 때 20 %의 감쇠인자를 가지고 이득조절을 수행하였다. 그러나 이 방법은 신호의 변화를 고려하지 않기 때문에 신호가 왜곡되는 경우가 발생한다. 따라서 Least Mean Square(LMS) 예측기를 사용하여 이전과 이후 프레임의 정보를 통한 적응적 신호 크기 예측으로 이득을 조절하는 것을 제안한다. 제안된 알고리즘의 성능 평가는 Perceptual Evaluation of Speech Quality(PESQ) 평가를 통하여 나타내었다.