• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.37-43
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• 1998

This paper proposes a new echo canceller that can be used in a full-duplex digital subscriber loop modem. The proposed echo canceller uses a NLMS-based parallel adaptation NLMS (PA-NLMS) algorithm. The PA-NLMS algorithm that an estimate of the nonstationarity to additive noise ratio (NNR) gained from two distinct NLMS processes is used to select the value of NLMS convergence-controlling parameter has been developed. Numerical results based on computer simulation show that the proposed algorithm has a convergence rate approaching that of the fastest possible NLMS process while improving on its MAC performance considerably.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.18-27
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• 2007

The conventional normalized least mean square (NLMS) algorithm is the most widely used for adaptive identification within a non-stationary input context. The convergence of the NLMS algorithm is independent of environmental changes. However, its steady state performance is impaired during input sequences with low dynamics. In this paper, we propose a new NLMS algorithm which is, in the steady state, insensitive to the time variations of the input dynamics. The square soot (SR)-NLMS algorithm is based on a normalization of the LMS adaptive filter input by the Euclidean norm of the tap-input. The tap-input power of the SR-NLMS adaptive filter is then equal to one even during sequences with low dynamics. Therefore, the amplification of the observation noise power by the tap-input power is cancelled in the misadjustment time evolution. The harmful effect of the low dynamics input sequences, on the steady state performance of the LMS adaptive filter are then reduced. In addition, the square root normalized input is more stationary than the base input. Therefore, the robustness of LMS adaptive filter with respect to the input non stationarity is enhanced. A performance analysis of the first- and the second-order statistic behavior of the proposed SR-NLMS adaptive filter is carried out. In particular, an analytical expression of the step size ensuring stability and mean convergence is derived. In addition, the results of an experimental study demonstrating the good performance of the SR-NLMS algorithm are given. A comparison of these results with those obtained from a standard NLMS algorithm, is performed. It is shown that, within a non-stationary input context, the SR-NLMS algorithm exhibits better performance than the NLMS algorithm.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.93-98
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• 2009

In this paper, we propose a new VSS-NLMS algorithm through a simple modification of the conventional NLMS algorithm, which leads to a low complexity algorithm with enhanced performance. The step size of the proposed algorithm becomes smaller as the error signal is getting orthogonal to the input vector. We also show that the proposed algorithm is an approximated normalized version of the KZ-algorithm and requires less computation than the KZ-algorithm. We carried out a performance comparison of the proposed algorithm with the conventional NLMS and other VSS algorithms using an adaptive channel equalization model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1203-1210
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• 1999

Coefficients of the adaptive filter are misadjusted by primary signals which are uncorrelated with reference signals of the adaptive filter. In this paper, the normalized sign algorithm is analyzed and compared with the NLMS algorithm by the steady state performance and the transient characteristics when target signals are included in primary signals. The excess mean square error of the NLMS algorithm is proportional to the power of target signals. That of normalized sign algorithm is proportional to the square root of the target signal power. However, the convergence speed of the normalized sign algorithm is slower than that of NLMS algorithm. In this paper, it is shown that theoretical analysis of the steady state performance and the transient characteristics are well consisted with the results of computer simulation.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.5 no.1
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• pp.25-36
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• 2006

This paper discusses the implementation and performance evaluation of a DSP-based digital beamformer using the Texas Instrument TMSC6711 DSP processor for smart antenna applications. Two adaptive beamforming algorithms which served as the brain for the beamformer, the Normalized Least-Mean-Square (NLMS) and the Constant Modulus Algorithms (CMA) were embedded into the processor and evaluated. Result shows that the NLMS-based digital beamformer outperforms the CMA-based digital beamformer: 1)For NLMS algorithm, the antenna steers to the direction of the desired user even at low iteration value and the suppression level towards the interferer increases as the number of iteration increase. For CMA algorithm, the beam radiation pattern slowly steers to the desired user as the number of iteration increased, but at arate slower than NLMS algorithm and the sidelobe level is shown to increases as the number of iteration increase. 2) The NLMS algorithm has faster convergence than CMA algorithm and the error convergence for CMA algorithm sometimes is subject to misadjustment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.1
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• pp.45-50
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• 2015

In this paper, we confirm the effective adaptive algorithm for tha active noise contorl (ANC) though the performance comparison between adaptive algorithms. Generally, the normalized least mean square (NLMS) algorithm has been widely used for an adaptive algorithm thanks to its simplicity and having a fast convergence speed. However, the convergence performance of the NLMS algorithms is often deteriorated by colored input signals. To overcome this problem, the affine pojection (AP) algorithm that updates the weight vector based on a number of recent input vectors can be used for allowing a higher convergence speed than the NLMS algorithm, but it is computationally complex. Thus, the proper algorithm were determined by the comparison between NLMS and AP algorithms regarding as the convergence performance and complexity. Simulation results confirmed that the noise reduction performance of NLMS algorithm was comparable to AP algorithm with low complexity. Therefore the NLMS algorithm is more effective for ANC system.

• Journal of Korea Multimedia Society
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• v.2 no.1
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• pp.99-108
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• 1999

In this paper, a new robust adaptive algorithm is proposed to improve the performance of AEC without computational burden. The proposed adaptive algorithm is based on NLMS algorithm, and its step-size is varied with the reference input signal power and the desired signal power. Its step-size is normalized by the sum of the powers of the reference input signal and the desired signal. When the near-end speaker's speech and noise are applied into the microphone, the step-size becomes small and the misalignment of coefficients are reduced. The convergence speed is comparable to NLMS algorithm at AEC application because the echo signals are attenuated about 10∼20 dBSPL. The characteristics of this algorithm is also analyzed and compared with conventional ones in this paper.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.49-58
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• 2012

This paper is on an improved orthogonal projection method which can cancel the acoustic feedback signals in the digital hearing aids. Comparing with the NLMS algorithm which is widely used for simplicity and stability, it shows that this method has the improvement of the convergence performances, and has small computational quantities, for signals with the large auto-correlation as speech signals. This uses the improved orthogonal projection algorithm which reduces the correlation of signals. To verify the convergence characteristics of the proposed algorithm, we simulated about various input signals. The acoustic feedback canceller has a 12-bit resolution with 64-tap adaptive FIR filter. And we compared the results of simulation for this algorithm with the ones for the NLMS algorithm. By these works, it is proved that the feedback canceller adopting the proposed algorithm shows about 3.5dB more high SNR than the NLMS algorithm in the colored input signals.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.159-162
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• 2010

This paper presents a new Kurtosis driven Variable Step-Size Normalized Least Mean Square (KVSSN-LMS) algorithm to prevent repeater from oscillation due to feedback signal of radio frequency (RF) repeater. To get better Mean Square Error (MSE) performance, step-size is adjusted using the kurtosis. The proposed algorithm shows the better performance of steady state MSE. The proposed algorithm shows a better ERLE performance than that of KVSS-LMS, VSS-NLMS, NLMS algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2388-2396
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• 2012

This paper is on an simplified orthogonal projection method which cancel the acoustic echo signals in the stereo acoustic echo canceller. Comparing with the NLMS algorithm which is widely used for simplicity and stability, it shows that this method has the improvement of the convergence performances for signals with the high auto-correlation, and has small computational quantities. To verify the convergence characteristics of the proposed algorithm, we simulated about various input signals. And we compared the results of simulation for this algorithm with the ones for the NLMS algorithm. By these works, it was proved that the stereo acoustic echo canceller adopting the proposed algorithm shows about 3dB more high ERLE than the NLMS algorithm for the white noise signals, and 5dB for the colored voice signals.