• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.3-8
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• 2016

We propose a modified form of the decision-directed least mean square (DD LMS) algorithm that is widely used in the optimization of self-adaptive equalizers, and show the modified version greatly improves the initial convergence properties of the conventional algorithm. Existing DD LMS regards the difference between a equalizer output and a quantization value for it as an error, and achieves an optimization of the equalizer based on minimizing the mean squared error cost function for the equalizer coefficients. This error generating method is useful for binary signal or a single-level signals, however, in the case of multi-level signals, it is not effective in the initialization of the equalizer. The modified DD LMS solves this problem by modifying the error generation. We verified the usefulness and performance of the modified DD LMS through experiments with multi-level signals under distortions due to intersymbol interference and additive noise.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1066-1068
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• 1996

This paper concerns about the active noise canceller via filtered-X LMS algorithm. There are various kinds of algorithms to implement a active noise canceller. Traditional LMS algorithms are not enough to implement a sharp noise cancellation characteristics. We simulates a filtered-X LMS algorithm and implements an algorithm to the TMS320C5x DSP processor and shows that result.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.88-94
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• 2013

In this paper, an efficient signal interference control technique to improve the convergence speed of LMS algorithm is introduced. The convergence characteristics of the proposed algorithm,whose coefficients are multiply adapted in a symbol time period by recycling the received data,are analyzed to prove theoretically the improvement of convergence speed. According as thestep-size parameter ${\mu}$ is increased, the rate of convergence of the algorithm is controlled. Increasing the eigenvalue spread has the effect of controlling down the rate of convergence of the adaptive equalizer and also increasing the steady-state value of the average squared error and also demonstrate the superiority of signal interference control to the filter algorithm increasing convergence speed by (B+1) times due to the data-recycling LMS technique.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.529-536
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• 2003

In this Paper, a new DCT HLMS DFE(Discrete Cosine Transform Hierarchical Least Mean Square Decision Feedback Equalizer) algorithm is proposed to improve the convergence speed and MSE(Mean Square Error) performance of a receive channel equalizer in ATSC(Advanced Television System Committee) 8VSB(Vestigial Side Band) digital terrestrial TV system. The proposed algorithm reduces the eigenvalue range of input data autocorrelation by transforming LMS (Least Mean Square) DFE into the subfilter of hierarchical structure. Moreover, the use of DCT and power estimation algorithm makes it possible to reduce the eigenvalue deviation of input data which results from distortion and delay of the receive signal in the miulti-path environment. Simulation results show that proposed DCT HLMS DFE has SNR improvement of approximately 3.8dB, 5dB and 2dB as compared to LMS DFE when the equalized symbol error rate is 0.2 in ATTC defined digital terrestrial TV broadcasting channels A, B and F, respectively.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.4
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• pp.17-21
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• 2002

Least mean square(LMS) algorithm one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency. in this paper, ie use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a high speed wavelet based adaptive algorithm with variable step size, which is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.199-203
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• 2002

Adaptive array is using the array of antenna elements spatially and its output is the sum of each antenna elements output signal which is multiplied by the controlled weight coefficients corresponding to each elements For the 4 elements equidistance linear array antenna system LMS and RLS algorithm was used as the adaptive instruction principles and the application results to the constant amplitude envelope signals such as BPSK can be seen that the computer simulation results are very fast in the convergence characteristics of directional patterns and the signal following characteristics.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.197-200
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• 2004

디지털 TV 전송 방식중의 하나인 ATSC 8-VSB 시스템의 등화기는 훈련신호가 존재하는 구간에서 LMS 알고리즘을 사용하는 DFE 적옹 등화기가 사용된다. 그러나 LMS 알고리즘은 그 수렴속도가 느리고 수렴 후 오차 수준이 다른 적응 알고리즘에 비해 높다는 단점이 있다. 본 논문에서는 LMS 알고리즘을 사용하는 DFE의 오차 수준을 낮추기 위한 선형 등화기 구조의 전 처리부(pre-processor)를 사용하여 필터 수렴 후의 DFE의 오차수준을 기존의 DFE보다 낮추었으며 제안된, DFE 구조의 성능을 컴퓨터 모의 실험을 통해 분석하였다.

• 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 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.