• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.315-321
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• 2004

In this study, we proposed an adaptive feedback cancellation algorithm for multi-band digital healing aids. The adaptive feedback canceller (AFC) is composed of an adaptive notch filter (ANF) for feedback detection and an NLMS (normalized least mean square) adaptive filter for feedback cancellation. The proposed feedback cancellation algorithm is combined with a multi-band hearing aid algorithm which employs the MDCT (modified discrete cosine transform) filter bank for the frequency-dependent compensation of hearing losses. The proposed algorithm together with the MDCT-based multi-channel hearing aid algorithm has been evaluated via computer simulations and it has also been implemented on a commercialized DSP board for real-time verifications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11C
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• pp.1127-1133
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• 2007

This paper proposes one of normalized QR-typed LMS (Least Mean Square) algorithms with computational complexity of O(N). This proposed algorithm shows the normalized property in terms of theoretical characteristics. This proposed algorithm is one of algorithms which normalize variance of input signal in terms of mean because QR-typed LMS is proportional to variance of input signal. In this paper, convergence characteristic analysis of normalized algorithm was made. Computer simulation was made by the algorithms used for echo canceller. Proposed algorithm has similar performance to theoretical value. And, we can see that proposed method shows similar one to performance of NLMS.by comparison among different algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.858-865
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• 2008

In this paper, Capacitive Telemetry RF Sensor System using Recursive Least Square (RLS) algorithm was proposed. General Telemetry RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Telemetry RF Sensor System adopts Integrated Circuit type, but there are many defects like complexity of structure and the limitation of large power consumption in some cases. In order to overcome these disadvantages, Telemetry RF Sensor System based on inductive coupling principle was proposed in this paper. Proposed Telemetry RF Sensor System is very simple because it consists of R, L and C and measures the changes of environment like pressure and humidity in the type of capacitive value. This system adopted RLS algorithm for estimation of this capacitive parameter. For the purpose of applying RLS algorithm, proposed system was mathematically modelled with phasor method and was quasi-linearized. As two parameters such as phase and amplitude of output voltage for estimation were needed, Phase Difference Detector and Amplitude Detector were proposed respectively which were implemented using TMS320C2812 made by Texas Instrument. Finally, It is verified that the capacitance of proposed telemetry RF Sensor System using RLS algorithm can be estimated efficiently under noisy environment.

• Journal of the Ergonomics Society of Korea
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• v.20 no.1
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• pp.45-62
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• 2001

This study suggests a genetic algorithm-based partial least squares (GA-based PLS) method to select the design variables for building a usability model. The GA-based PLS uses a genetic algorithm to minimize the root-mean-squared error of a partial least square regression model. A multiple linear regression method is applied to build a usability model that contains the variables seleded by the GA-based PLS. The performance of the usability model turned out to be generally better than that of the previous usability models using other variable selection methods such as expert rating, principal component analysis, cluster analysis, and partial least squares. Furthermore, the model performance was drastically improved by supplementing the category type variables selected by the GA-based PLS in the usability model. It is recommended that the GA-based PLS be applied to the variable selection for developing a usability model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.3
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• pp.103-109
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• 2003

The validity of measured data is fundamental factor for the power system automation Measured values could have errors that are caused by the communication errors and malfunctioning measuring devices. The accuracy and reliability of measured values at a substation is an important condition for robust and fault tolerant automata. Errors can be reduced by state estimation, however, global reliability of state estimation goes down in case of the existence of some bad data In this paper, a least square state estimation and bad sensor detection algorithm based on chi-square theory, ale proposed and it is applied to a domestic 154kV distribution substations. A simulator together with user friendly graphic users interface is developed using C language and Visual Basic. TCP/IP is equipped for future connection with other operation systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.288-295
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• 2013

In this paper, we compare the existing channel estimation technique for 4S (Ship to Ship, Ship to Shore) maritime communications under AWGN channel model, Rician fading channel model, and Rayleigh fading channel model respectively. In general, the received signal is corrupted by multipath and ISI (Inter Symbol Interference). The estimation of a time-varying multipath fading channel is a difficult task for the receiver. Its performance can be improved if an appropriate channel estimation filter is used. The simulation is performed in MATLAB. In this simulation, we use the popular estimation algorithms, LMS (Least Mean Square) and RLS (Recursive Least-Squares) are compared with respect to AWGN, Rician and Rayleigh channels.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.10
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• pp.863-871
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• 2017

LMS (least mean square) algorithm widely used in the AVCS (active vibration control system) of helicopters calculates control input using the forward path transfer function and error signal. If the error signal is sinusoidal, it can be represented as the combination of cosine and sine functions with frequency and phase synchronized with the reference signal. The control input also has the same frequency, therefore control algorithm can be simply implemented if the cosine and the sine amplitudes of the control input are calculated and the frequency and phase of the reference signal are used. Calculation of the control input is implemented as simple matrix operation and the change of the control command is slower than the frequency of the error signal, consequently control algorithm can be operated at lower frequency. The signal processing algorithm extracting cosine and sine components of the error signals are modeled using Simulink and PIL (processor-in-the-loop) mode simulation was executed for real-time performance evaluation.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.134-136
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• 1986

In this paper, a new power spectral estimation technique is presented. At first, by transforming the original data with the Karhunen-Loeve Transform(KLT), we can reduce the amount of the redundant information. Next, by modeling the transformed data by means of the autoregressive(AR) model and then applying the least-squares parameter estimation algorithm to this model, even more accurate spectrum estimates can be obtained. The KLT is the optimum transform for signal representation with respect to the mean-square error criterion. And the least-squares method is used to overcome the inherent shortcomings of popular burg algorithm.