• Journal of Digital Convergence
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• v.10 no.11
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• pp.377-382
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• 2012

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.331-335
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• 2001

In this paper, we propose two novel blind LMS algorithms, called exponential step sire LMS algorithms (ES-LMS), for adaptive array antennas whose convergence speed is increased, hence they are much more capable of tracking the desired signal than the conventional LMS algorithms. Both of the algorithms require neither spatial knowledge nor reference signals since they use the finite symbol property of digital signal. Computer simulations were carried cot in CDMA environment affected by multi-path Rayleigh fading to verify the performance of the two proposed algorithms.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.5
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• pp.12-19
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• 1982

In general the design methods of adaptive filter are divided into two categories, one is based upon the local parameter optimization theory and the other is based upon stability theory. Among the various design techniques, the LMS algorithm by steepest-descent method which is based upon local parameter optimization theory is used widely. In designing the adaptive filter, the most important factor is the convergence rate of the algorithm. In this paper a new algorithm is proposed to improve the convergence rate of adaptive firter compared with the commonly used LMS algorithm. The faster convergence rate is obtained by adjusting the adaptation gain of LMS algorithm. And various aspects of improvement of the adaptive filter characteristics are discussed in detail.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.315-318
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• 2001

We propose two new blind LMS and MMSE algorithms called projection-based least mean square (PB-LMS) and projection-based minimum mean square error (PB-MMSE) for smart antennas. Both algorithms employ the finite constellation property of digital signal to transform the conventional LMS and MMSE algorithms into blind algorithms. Computer simulations were carried out in the AWGN channel and Rayleigh fading channel with AWGN in CDMA environment to verify the performance of the two proposed algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.90-94
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• 2008

It is well-blown that the convergence rate gets worse when an input signal to an adaptive filter is correlated. In this paper we propose a new adaptive filtering algorithm that makes the convergence rate much improved even for highly correlated input signals. By introducing an orthogonal constraint between successive input signal vectors we overcome the slow convergence problem of the LMS algorithm with the correlated input signal. Simulation results show that the proposed algerian yields fast convergence speed and excellent tracking capability under both time-invariant and time-varying environments, while keeping both computation and implementation simple.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4
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• pp.60-66
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• 1998

본 연구에서는 임펄스 잡음 환경 하에서, 대표적인 Bussgang계열의 블라인드 등화 알고리즘인 LMS-Sato 및 LMS-CMA 블라인드 등와 알고리즘의 수렴특성을 컴퓨터 모의 실험을 통하여 살펴보았다. LMAD-Sato 및 LMAD-CMA 블라인드 등화 알고리즘을 유도 하고, 동일한 조건하에서 그 수렴특성을 살펴보았다. 16-QAM 데이터에 대한 실험 결과 임 펄스 잡음 환경 하에서 LMAD 형태의 블라인드 등화 알고리즘이 LMS 형태의 블라인드 등 화 알고리즘 보다 안정적인 수렴특성을 보여 주었다. 또한, normalized 형태의 LMAD-Sato 및 CMA 블라인드 등화 알고리즘을 제안하였으며, 실험 결과 이들 알고리즘들이 임펄스 잡 음 환경에서 LMAD 형태의 알고리즘 보다 더 우수한 수렴 특성을 보여 주었다.

• The Journal of the Acoustical Society of Korea
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• v.7 no.2
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• pp.39-50
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• 1988

It is proposed to use a pair of frequency-domain adaptive digital filters to estimate the magnitude squared coherence (MSC) functions of two signals. Such a method requires less computations than the LMS-MSC algorithm in which the least mean square (LMS) algorithm is applied in the time domain to compute the coefficients of a pair of adaptive digital filters. The frequency-domain adaptive digital filtering algorithms considered in this paper include the constrained frequency domain LMS (CFLMS) and the unconstrained frequency domain LMS (UFLMS) algorithms. The performance of the proposed methods are compared with those of the LMS-MSC algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.95-101
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• 2009

Among the adaptive noise cancellers (ANC), the least mean square (LMS) algorithm has probably become the most popular algorithm because of its robustness, good tracking properties, and simplicity of implementation. However, it has non-uniform convergence and a trade-off between the rate of convergence and excess mean square error (EMSE). To overcome these shortcomings, a number of variable step size least mean square (VSSLMS) algorithms have been researched for years. These LMS algorithms use a complex variable step method approach for rapid convergence but need high computational complexity. A variable step approach can impair the simplicity and robustness of the LMS algorithm. The proposed instantaneous gain control (IGC) algorithm uses the instantaneous gain value of the original signal and the noise signal. As a result, the IGC algorithm can reduce computational complexity and maintain better performance.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.815-821
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• 2009

Information processing in variable and noisy environments is usually accomplished by means of adaptive filters. Among various adaptive algorithms, Least Mean Square (LMS) has become the most popular for its robustness, good tracking capabilities and simplicity, both in terms of computational load and easiness of implementation. In practical application of the LMS algorithm, the most important key parameter is the Step Size. As is well known, if the Step Size is large, the convergence rate of the algorithm will be rapid, but the steady state mean square error (MSE) will increase. On the other hand, if the Step Size is small, the steady state MSE will be small, but the convergence rate will be slow. Many researches have been proposed to alleviate this drawback by using a variable Step Size. In this paper, a new variable Step Size LMS(VSSLMS) called Categorized VSSLMS (CVSSLMS) is proposed. CVSSLMS updates the Step Size by categorizing the current status of the gradient, hence significantly improves the convergence rate. The performance of the proposed algorithm was verified from the view point of convergence rate, Excessive Mean Square Error(EMSE), and complexity through experiments.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.280-282
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• 1999

적응 횡단선 심볼간의 채널에 발생하는 상호 심볼간 간섭을 억압하기 위해 LMS 알고리즘을 사용한다. 이 알고리즘은 원하는 응답과 실제 출력간의 차인 에러를 이용하여 탭 가중치 조절 메카니즘을 통해 탭 가중치를 갱신함으로서 효과적으로 간섭을 제거하였다. 본 논문은 상호 심볼간 간섭을 효율적으로 억압해온 기존의 LMS알고리즘에 다계층 퍼셉트론 신경망을 조합 한 새로운 LMSBP 알고리즘을 제안하였으며, 제안된 알고리즘을 토해 탭 가중치 갱신이 보다 효율적으로 이루어짐을 알 수 있다. 시뮬레이션 결과를 통해 제안된 알고리즘의 평균 자승 에러의 수렴 특성이 LMS 알고리즘을 이용한 수렴특성보다 우월하다는 것을 나타내었다.