• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1007-1012
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• 2003

In order to accelerate the convergence speed of the conventional BP algorithm, constrained optimization techniques are applied to the BP algorithm. First, the noise-constrained least mean square algorithm and the zero noise-constrained LMS algorithm are applied (designated the NCBP and ZNCBP algorithms, respectively). These methods involve an important assumption: the filter or the receiver in the NCBP algorithm must know the noise variance. By means of extension and generalization of these algorithms, the authors derive an adaptive error-constrained BP algorithm, in which the error variance is estimated. This is achieved by modifying the error function of the conventional BP algorithm using Lagrangian multipliers. The convergence speeds of the proposed algorithms are 20 to 30 times faster than those of the conventional BP algorithm, and are faster than or almost the same as that achieved with a conventional linear adaptive filter using an LMS algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1468-1476
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• 1997

In mobile communication systems, the Reduced State Sequence Estimation(RSSE) receiver must be able to track changes in the channel. This is carried out by the adaptive channel estimator. However, when the tentative decisions are used in the channel estimator, incorrect decisions can cause error propagation. This paper presents a new channel estimator using the path history in the Viterbi decoder for preventing error propagation. The selection of the path history in the Viterbi decoder for preventing error propagation. The selection of the path history for the channel estimator depends on the path metric as in the decoding of the Viterbi decoder in RSSE. And a discussion on the channel estimator with different adaptation algorithms such as Least Mean Square(LMS) algorithm and Recursive Least Square(RLS) algorithm is provided. Results from computer simulations show that the RSSE receivers using the proposed channel estimator have better performance than the other conventional RSSE receiver, and that the channel estimator with RLS algorithm is adequate for multipath fading channel.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.57-60
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• 2003

We have proposed the adaptive noise reduction algorithm using the MDFT. The algorithm proposed use the linear prediction coefficients of the AR method based on Sign algorithm that is the modified LMS instead of the least mean square(LMS). The signals with a random noise tracking performance are examined through computer simulations and confirmed that the high speed adaptive noise reduction processing system is realized with rapid convergence.

• The Journal of the Acoustical Society of Korea
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• v.34 no.5
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• pp.403-409
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• 2015

In this paper, we propose Packet Loss Concealment (PLC) method using adaptive signal scale estimation for performance improvement of G.711 PLC. The conventional method controls a gain using 20 % attenuation factor when continuous loss occurs. However, this method lead to deterioration because that don't consider the change of signal. So, we propose gain control by adaptive signal scale estimation through before and after frame information using Least Mean Square (LMS) predictor. Performance evaluation of proposed algorithm is presented through Perceptual Evaluation of Speech Quality (PESQ) evaulation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.12 s.354
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• pp.1-8
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• 2006

In this paper, we propose carrier phase synchronization algorithm which are base on turbo coded system for DVB-RCS. There have been two categories of phase estimator, single estimator outside turbo code decoder and multiple estimators inside turbo code decoder. In single estimator, we use the estimation algorithm that ML(Maximum Likelihood) and LMS(Least Mean Square), also three different soft decision methods are proposed. Multiple estimator apply PSP(Per Survivor Processing) algorithm additionally. We compared performance between single estimator and Multiple estimator in AWGN channel. We presented the two methods of PSP algorithm for performance elevation. First is the Bi-directional channel estimation and second is binding method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.305-344
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• 2008

This paper presents the active control of flexible beam vibration. The beam was excited by a steady-state point force by mini shaker and the control was performed by mini shaker. To perform active control, least-mean-square (LMS) algorithm was used because it can easily obtain the complex transfer function in real-time. So an adaptive controller based on Filtered-X LMS algorithm was used and the controller was defined by minimizing the square of the response at a location of error sensor. In order to fine out performance tendency, input amplitude was changed in several cases and active vibration control was performed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1061-1066
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• 2014

Transmission characteristics of the sound propagation is very complicate and sparse in shallow water. To increase the performance of underwater acoustic communication system, lots of channel estimation technique has been proposed. In this paper, we proposed the channel estimation based on LMS(Least Mean Square) algorithm which has faster convergence speed than conventional sparse-aware LMS algorithms. The proposed method combines $L_p$-norm LMS with soft decision process. Simulation was performed by using the sound velocity profile which acquired in real sea trial. As a result, we confirmed that the proposed method shows the improved performance and faster convergence speed than conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.9-22
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• 2019

In this paper, we propose a method that can be applied to the efficient implementation of multi-channel active noise controller. Since the normalized MFxLMS (Modified Filtered-x Least Mean Square) algorithm for the multi-channel active noise control requires a large amount of computation, the difficulty has lied in implementing the algorithm using a low-cost MCU (Microcontoller Unit). We implement the multi-channel active noise controller efficiently by optimizing the software based on the features of the MCU. By maximizing the usage of single-cycle MAC (Multiply- Accumulate) operations and minimizing move operations of the delay memory, we can achieve more than 3 times the performance in the aspect of computational optimization, and by parellel processing using the auxillary processor included in the MCU, we can also obtain more than 4 times the performance. In addition, the usage of additional parts can be minimized by maximizing the usage of the peripherals embedded in the MCU.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.377-382
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• 2012

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.

• Journal of Korean Society for Atmospheric Environment
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• v.2 no.3
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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.