• 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 Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.163-166
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• 2010

본 논문에서는 현재 상용화 되어있는 WCDMA용 ICS (Interference Cancellation System) 중계기의 성능 개선을 위한 개선된 LMS 알고리즘을 연구하였다. ICS 중계기의 수신으로 입력되는 신호는 수신 신호와 궤환되어 입력되는 신호로 구성된다. 이렇게 입력되는 궤환 신호를 LMS와 같은 적응형 채널 추정 알고리즘을 통해 제거하는 기술이 ICS 중계기의 핵심 요소이다. 중계기의 저비용 및 단순화를 위해서는 기존에 사용되어온 적응형 채널 추정 알고리즘의 단순화가 필요하다. 실험을 통해 기존 NLMS 알고리즘 및 계산 복잡도 감소를 위해 수정된 LMS 알고리즘을 MSE (Mean Square Error) 기준에서 성능 비교를 하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.102-105
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• 2000

본 논문에서는 잡음환경에서의 음성신호복원(Speech Enhancement) 시스템 구현을 목적으로 한다 이를 위한 적응필터로서 LMS(Least Mean Square)알고리즘 FIR필터를 제안한다. 또 정밀 필터로서 신경망 필터를 제안한다. 잡음환경에서의 음성신호 복원 시스템은 잡음에 의해 왜곡된 음성신호에서 잡음성분만을 제거함으로써 음성신호를 복원하는 시스템이다. 일반적으로 잡음은 시변특성과, 비선형적인 전달특성을 갖는다. 그러므로 파라미터가 고정된 필터로는 제어하기가 힘들다. 이러한 이유로 본 논문에서는 LMS알고리즘 적응필터를 적용한다. 신경망 필터는 오차 역전파 학습 알고리즘에 의해 오차를 최소화하는 방향으로 필터의 파라미터를 수정한다. 제안한 필터로 잡음환경에서의 음성신호복원 시스템을 구성하고, 실험을 통해 필터의 성능을 확인한다.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.2
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• pp.32-38
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• 2000

One of the most popular algorithm in adaptive signal processing is the least mean square(LMS) algorithm. The majority of these papers examine the LMS algorithm with a constant step size. The choice of the step size reflects a tradeoff between misadjustment and the speed of adaptation. Subsequent works have discussed the issue of optimization of the step size or methods of varying the step size to improve performance. However there is as yet no detailed analysis of a variable step size algorithm that is capable of giving both the adaptation speed and the convergence. In this paper we propose a new variable step size algorithm where the step size adjustment is controlled by the gradient of error square. The proposed algorithm is performed in the Walsh-Hadamard domain in real-valued orthogonal transform because of fast convergence. The simulation results using the new algorithm for noise canceller system is described. They are compared to the results obtained by other algorithms. It is shown that the proposed algorithm produces good results compared with conventional algorithms.

• 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 SP
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• v.43 no.1 s.307
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• pp.91-100
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• 2006

A scheme is proposed for implementing the block LMS algorithm in a block floating point framework that permits processing of data over a wide dynamic range at a processor complexity and coat as low as that of a fixed point processor. The proposed scheme adopts appropriate formats for representing the filter coefficients and the data. Using these and a new upper bound on the step size, update relations for the filter weight mantissas and exponent are developed, taking care so that neither overflow occurs, nor are quantifies which are already very small multiplied directly. It is further shown how the mantissas of the filter coefficients and also the filter output can be evaluated faster by suitably modifying the approach of the fast block LMS algorithm

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.408-414
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• 2013

The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

• Journal of IKEEE
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• v.15 no.4
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• pp.293-298
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• 2011

In the paper, we propose a new CMF(Constant Modulus Fourth) algorithm for WCDMA(Wideband Code Multiple Access) RF(Radio Frequency) Repeater. CMF algorithm is proposed by modifying the CMA(Constant Modulus Algorithm) algorithm and improved performances are achieved by properly adjusting step size values. The steady state MSE(Mean Square Error) performance of the proposed CMF algorithm with step size of 0.35 is about 4dB better than that of the conventional CMA algorithm. And the proposed CMF algorithm requires 400~1100 less iterations than the LMS(Least Mean Square) and NLMS(Normalized Least Mean Square) algorithms at MSE of -25dB.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.25-36
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• 1996

Conventional radial-basis-function networks and fuzzy systems have serious problems in dealing with the non1inea:r approximations on high-dimensional spaces due to the explosive increase of the number of hidden nodes or fuzzy IF-THEN rules. In order to avoid such problems, this paper proposes a tree-structured intelligent system in which semi-local basis functions form its basic elements, and develops a training algorithm for the proposed system based on the modified genetic algorithm and LMS rule. Theoretical analysis is performed on the approximation capability of the proposed system, together with experimental studies which demonstrate the effectiveness of the developed methodology.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7C
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• pp.562-568
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• 2008

This paper proposes the scheme which obtain the coefficients of TDL filter and two normalization algorithms among methods which get solution of equivalent Wiener-Hopf Equation in Gram-Schmidt algorithm. Compared to the conventional NLMS algorithm, normalizes with sum of power of inputs, the presented algorithms normalize using sums of eigenvalues. Using computer simulation, we perform an system identification in an unstable environment where two poles are located in near position outside unit circle. Consequently, the proposed algorithms get the coefficients of TDL filter in Gram-Schmidt algorithm recursively and show better convergence performance than conventional NLMS algorithm.