• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.3
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• pp.171-177
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• 2016

Noise problem that occurs in living environment is a big trouble in the economic, social and environmental aspects. In this paper, the filtered-X LMS algorithms, the adjoint LMS algorithms, and the robust adjoint LMS algorithms will be introduced for applications in active noise control(ANC). The filtered-X LMS algorithms is currently the most popular method for adapting a filter when the filter exits a transfer function in the error path. The adjoint LMS algorithms, that prefilter the error signals instead of divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of multi-channel ANC systems such as the 3D space. To improve performance of the adjoint LMS ANC system, an off-line measured transfer function is connected parallel to the LMS filter. This parallel-fixed filter acts as a noise controller only when the LMS filter is abnormal condition. The superior performance of the proposed system was compared through simulation with the adjoint LMS ANC system when the adaptive filter is in normal and abnormal condition.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.549-554
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• 2014

In the paper, we propose a new Signed LMS(Least Mean Square) algorithm for ICS(Interference Cancellation System). The proposed Signed LMS algorithm improved performances by adjusting step size values. At the convergence of 1000 iteration state, the MSE(Mean Square Error) performance of the proposed Signed LMS algorithm with step size of 0.067 is about 3 ~ 18 dB better than the conventional LMS, CMA algorithm. And the proposed Signed LMS algorithm requires 500 ~ 4000 less iterations than the and LMS and CMA algorithms at MSE of -25dB.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.2
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• pp.146-155
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• 2012

The filtered-x LMS(FX-LMS) algorithm has been applied to the active noise control(ANC) system in an acoustic duct. This algorithm is designed based on the FIR(finite impulse response) filter, but it has a slow convergence problem because of a large number of zero coefficients. In order to improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct since the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filtered-u LMS algorithm(FU-LMS) based on infinite impulse response(IIR) is developed by considering the backward acoustic propagation. This algorithm, unfortunately, generally has a stability problem. The stability problem was improved by using an error smoothing filter. In this paper, the recursive LMS algorithm with variable step size and smoothing error filter is designed. This recursive LMS algorithm, called FU-VSSLMS algorithm, uses an IIR filter. With fast convergence and good stability, this algorithm is suitable for the ANC system in a short acoustic duct such as the intake system of an automotive. This algorithm is applied to the ANC system of a short acoustic duct. The disturbance signals used as primary noise source are a sinusoidal signal embedded in white noise and the chirp signal of which the instantaneous frequency is variable. Test results demonstrate that the FU-VSSLMS algorithm has superior convergence performance to the FX-LMS algorithm and FX-LMS algorithm. It is successfully applied to the ANC system in a short duct.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.32-39
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• 2009

In this thesis, design effective elimination interference algorithm of ICS repeat system for repeater that improve frequency efficiency. Gennerally, LMS Algorithm apply to ICS repeat system. Error convergence speed and accuracy of LMS Algorithm are influenced by reference signal. For improve LMS Algorithm, suggest Adaptive searching channel estimate algorithm. For using channel characteristic, adaptive searching channel estimate algorithm make reference signal similar interference signal by convolution operation and complement LMS algorithm demerit. For make channel similar pratical channel, apply Jake's Rayleigh multi-path model. LMS algorithm and suggested adaptive searching channel estimate algorithm that have 16 taps apply to ICS repeat system under Rayleigh multi-path channel, so simulate with MATLAB. According to simulate, ICS repeat system with LMS algorithm show -40 dB mean square error convergent after 110 datas iteration and ICS repeat system with adaptive searching channel estimate algorithm show -80 dB mean square en-or convergent after 120 datas iteration. Analyze simulation result, suggested adaptive searching channel estimate algorithm show 40 dB accuracy than LMS algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.627-634
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• 2007

When a higher-order modulation scheme (16QAM or 64QAM) is applied to the communications system using the nonlinear high power amplifier (HPA), the performance can be degraded by the nonlinear distortion of the HPA. The nonlinear distortion can be compensated by the adaptive nonlinear Volterra equalizer using the low-complexity LMS algorithm at the receiver. However, the LMS algorithm shows very slow convergence performance. So, in this paper, the parallel M-band discrete wavelet transformed LMS algorithm is proposed in order to improve the convergence speed. Throughout the computer simulations, it is shown that the convergence performance of the proposed method is superior to that of the conventional time-domain and transform-domain LMS algorithms.

• Educational Technology International
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• v.25 no.1
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• pp.67-92
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• 2024

This study aims to verify the practical effectiveness of learning management system (LMS) by introducing a LMS enhancing digital assessment utilizing automatic item generation in order to strengthen college student's mathematics performance. Teaching assisted with digital assessment in the LMS was applied to college mathematics classes, and the research question is whether or not students in the classes utilizing the LMS perform better than the regular classes. In particular, a calculus course, which is the foundation of important artificial intelligence technology in the future, was utilized in this study. The participants of this study were 248 freshmen in science and engineering who were taking calculus courses at a small to mid-size university. A total of 156 freshmen were selected after applying a propensity score matching method (PSMM), 78 from classes utilizing the LMS and 78 from regular classes without the LMS assisted with the digital assessment. As a result, it was found that there was a statistically significant difference in the math academic growth of students who used the LMS and those who did not. In other words, when LMS was used in calculus, students' academic growth was greater. The results of this study are meaningful in that they observed students' academic growth and confirmed that LMS enables a positive role in students' academic growth. In addition, if digital assessment is strengthened and LMS that enables individualized learning analysis is introduced and implemented in educational institutions, it is expected to play a major role in strengthening students' academic performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.231-239
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• 2009

The filtered-x LMS (FX-LMS) algorithm has been applied to the active noise control (ANC) system in an acoustic duct. This algorithm is designed based on the FIR (finite impulse response) filter, but it has a slow convergence problem because of a large number of zero coefficients. In order to improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct since the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filteredu LMS algorithm (FU-LMS) based on infinite impulse response (IIR) is developed by considering the backward acoustic propagation. This algorithm, unfortunately, generally has a stability problem. The stability problem was improved by using an error smoothing filter. In this paper, the recursive LMS algorithm with variable step size and smoothing error filter is designed. This recursive LMS algorithm, called FU-VSSLMS algorithm, uses an IIR filter. With fast convergence and good stability, this algorithm is suitable for the ANC system in a short acoustic duct such as the intake system of an automotive. This algorithm is applied to the ANC system of a short acoustic duct. The disturbance signals used as primary noise source are a sinusoidal signal embedded in white noise and the chirp signal of which the instantaneous frequency is variable. Test results demonstrate that the FU-VSSLMS algorithm has superior convergence performance to the FX-LMS algorithm and FX-LMS algorithm. It is successfully applied to the ANC system in a short duct.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.295-299
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• 2004

In this paper, we compare and analyze the LMS ard RLS algorithm of IEEE802.15.3(HDR-WPAN) system. The LMS algorithm have two merits that easily embody and not complex, but convergence speed is slow. The RLS algorithm have fast convergence speed, but very complex. When equalization using LMS algorithm, it can achieve adaptive equalization after 250 sample in fading environment, but case of RLS algorithm can achieve adaptive equalization after just 50 sampls. The computer simulation proved that adaptive equalizer to fast equalization and stability of HDR-WPAN system is more effective using RLS algorithm then LMS algorithm.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.278-283
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• 2010

In this paper, we designed and proposed framework of extended user model to support student tailored learning in ubiquitous environment. For the purpose, existents model that is domain model, user model, adaptation model and interaction model connected to LMS(Learning Management System) and LCMS(Learning Contents Management System). Students information management process that is extended user model is in between LMS and adaptive learning system. And the process connected u-LMS to use u-learning. u-LMS and u-LCMS could support the learning contents through exchange the contents according to connect and request from the students.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2C
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• pp.150-159
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• 2002

This paper presents the convergence time, SER(Symbol Error Rate), MSE(Mean Square Error), hardware complexity and step-size(${\mu}$) about various LMS(Least Mean Square) algorithms in FS-DFE(Fractionally Spaced-Decision Feedback Equalize) for Cable Modem based on MCNS(Multimedia Cable Network System) DOCSIS(Data Over Cable Service Interface Specification) v1.0/v1.1 standards. We designed and simulated using ${SPW}^{TM}$ and synthesized using STD90 library through ${SYNOPSYS}^{TM}$. And also, we adopted the time-multiplexed multiplication and tap shared architecture in order to achieve the low hardware complexity. Simulation results show that DS-LMS algorithms[1][3] is the optimum solution about performace and hardware size. in high order QAM applications. Finally, we achieved area saving about 58% using DS-LMS algorithm compare with conventional equalizer architecture.