• The Journal of the Acoustical Society of Korea
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• v.16 no.2E
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• pp.14-20
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• 1997

The future teleconferencing systems will need an appropriate system which controls properly the acoustic echo for the convenient communication. The conventional acoustic echo cancellation algorithms involve large adaptive filters identifying the impulse response of the echo path. The use of adaptive IIR filters appears to be a reasonable way to reduce computational complexity. Effective cancellation of acoustic echo presented in teleconferencing system requires that adaptive filters have a rapid convergence speed. One of the main problems of acoustic echo cancellation techniques is that the convergence properties degrade for an highly correlated signal input such as speech signals. By the way, the introduction of linear prediction filers onto the structure of the acoustic echo cancellation represents one approach to decorrelate the speech signal. And variable step-size LMS algorithm improves the convergence speed through a little increasing of computational complexity. In this paper, we applied these two methods to the acoustic echo canceller(AEC) and showed that these methods have better performances than the conventional AEC.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.42-49
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• 1997

A conventional adaptive noise canceller (ANC) using LMS algorithm suffers from the misadjustment of adaptive filter weights due to the gradient-estimate noise by input speech signal at steady state. In this paper, an ANC is proposed which uses the combination of VSLMS (variable step size LMS) and SA (sign algorithm) to improve steady state performance and convergence rate. SA algorithm is applied in speech region to prevent the weights from perturbing by output speech of ANC and VSLMS algorithm is applied to improve convergence rate and channel tracking ability in silence region and adaptive transient region. In compute rsimulation, the performance of the proposed VSLMS-SA combination algorithm is much better than LMS algorithm and the algorithm, recently proposed by greenberg, with adaptation step-size parameter determine dby sum method in convergence rate, channel tracking and steady state performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.12
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• pp.1744-1749
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• 2013

Acoustic feedback is perceived as whistling or howling, which is a major complaint of hearing-aids users. Acoustic feedback cancellation is important in hearing-aids because acoustic feedback degrades performance of the hearing aid device by reducing maximum insertion gain. Adaptive systems for estimate acoustic feedback path and feedback suppression algorithms have been proposed in order to solve this problem. A typical feedback cancellation algorithm is LMS(least mean squares) because of its computational efficiency. However it has problem of convergence performance in high correlated input signal. In this paper, we propose a new variable step-size normalized LMS(least mean squares) algorithm using VAD(voice activity detection) to overcome the limitation of the LMS algorithm. The VAD algorithm is GSAP(global speech absence probability) and the feedback cancellation algorithm is normalized LMS. The proposed algorithm applies different step-size between voice and non-voice using VAD, for high stability, fast convergence speed and low misalignment when correlated inputs, such as speech. The result of simulation with white noise mixed speech signal, the proposed algorithm shows high performance then traditional algorithm in terms of stability, convergence speed and misalignment.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.153-156
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• 2002

An adaptive predistorr is proposed to compensate for the nonlinear distortion of a high power amplifier (HPA) in 16 QAM system. It fumed out that the proposed predistorter using a variable step-size least mean square (VSSLMS) algorithm is stable and can reduce the Total Distortion (TD) to 0. 1dB at the HPA output backoff=0.0 dB.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.201-201
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• 2004

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.111-116
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• 2009

In this paper, we propose a phase offset estimation algorithm which is based on turbo coded digital broadcasting system. The phase estimator is an estimator outside turbo code decoder using LMS (Least Mean Square) algorithm to estimate the phase of next state. While the conventional LMS algorithm with a fixed step size is easy implemented, it has weak points that are difficult the channel estimation and tracking in the multipath environment. To resolve this problem, we propose new phase offset estimation method with a variable step size LMS (VS-LMS). Additionally, we propose a scheme which consists of a conventional LMS. The performance is verified by computer simulation according to a fixed phase offset and a increased phase offset, the proposed algorithm improve the bit error rate performance than the conventional algorithm.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.33-40
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• 1996

In this paper, we resolved a trade-off problem of the blind equalizer based on the stop-and-go algorithm that is commonly used for QAM demodulation in CATV receiver. The stop-and-go algorithm has used the LMS(least mean square) algorithm in the updating operation of tap weights so that the structure of equalizer is simple, but there is a trade-off between convergence speed and steady state error as in the typical LMS algorithm. We used the variable step size algrithm to improve the convergence speed with the steady state error in the constant level. With respect to the same level of the steady state error, the variable step size stop-and-go algortihm improved convergence speed by about $36%{\sim}56%$ as compared with that of the constant step size algortihm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.823-828
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• 1992

A novel steepest descent adaptive filter algorithm, which uses the instantaneous stochastic gradient for the steepest descent direction, is derived from a newly devised performance index function. The performance function for the new algorithm is improved from that for the LMS in consideration that the stochastic steepest descent method is utilized to minimize the performance index iterativly. Through mathematical analysis and computer simulations, it is verified that there are substantial improvements in convergence and misadjustments even though the computational simplicity and the robustness of the LMS algorithm are hardly sacrificed. On the other hand, the new algorithm can be interpreted as a variable step size adaptive filter, and in this respect a heuristic method is proposed in order to reduce the noise caused by the step size fluctuation.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.967-970
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• 2001

본 논문에서는 적응 필터의 계수 갱신에서 가변 블록을 사용하는 방법을 제안하였다. 데이터 블록의 길이는 MSE 학습곡선의 시정수에 비례하도록 하였다. 이 방법에서는 적응 필터가 정상상태로 접근함에 따라 스텝사이즈를 조정하여 필터계수 갱신의 횟수를 줄일 수 있다. 제안한 방법의 유용성을 입증하기 위한 컴퓨터모의 실험을 통해 기존의 최적 스텝사이즈 수열을 이용한 알고리듬과 가변 스텝사이즈 알고리듬과 성능을 비교하였다. 그리고 MSE 의 초기값을 최소화하는 최적 초기 스텝사이즈를 유도하였다. 유도된 최적 스텝사이즈를 가변 스텝사이즈 알고리듬에 적용, 그 성능을 평가 하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.407-416
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• 2000

Adaptive digital filtering and noise cancelling technique using a tree structured filter bank are presented to reduce a undesirable aliasing due to the decimation of filtered output and improve the performance in terms of mean-square error and the convergence speed using a aliasing canceller. A signal is split into two subband by analysis filter bank and decimated by decimator and reconstructed by interpolation technique and synthesis filter bank. A variable step-size LMS algorithm is used to improve the convergence speed in case of existing the measurement noise in desired input of filter. It is shown by computer simulation that the proposed subband structure in this paper is superior to conventional subband filter structure in terms of mean-square error and convergence speed.