• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.623-626
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• 1998

NLMS algorithm is degraded by the ambient noises and the near-end speech signals. In this paper, a robust acoustic echo cancellation algorithm is proposed. To enhance the echo cancellation performance, the step size of the proposed algorithm is normalized by the sum o fthe power of the reference signals and the primary signals. as results of comparing the excess mean square errors, it is shown that the proosed algorithm can enhance the performance of cancelling the echo signals. Some experiments, which is used multimedia personal computer, are carried out. As results of experiments, the proposed algorithm shows better performance than conventional ones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.876-883
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• 1996

Adaptive FIR filters are widely used in the echo canceller. But, most of practical systems have the transfer function composed of poles and zeros. In that case, adaptive IIR filters may be more efficient rather than FIR fiters. In this paper, a recently developed C-HARF algorithm is used to implement an adaptive IIR echo canceller. The proposed convergence of the algorithm make it attractive for this application. Extensive computer simulations show that C-HARF algorithm performs better than the NLMS algorithm after convergence, although C-HARF algorithm converges more slowly.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.37-41
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• 2002

In this paper, we made shorter EDT(early decay time) of room reverberation curve using multiple-channel. The speech signal was processed inverse filtering with full-band and sub-band in the basis MINT, and then the multiple-channel adaptive filters were used LMS (Least Mean Square) and NLMS (Normalized Least Mean Square) algorithm. Experimental results, we could get 1/3 of time reduction at 20dB level in the reverberation curve using full-band NLMS when two microphones were used. Also, it is shown that the speech articulation was improved 80% from the test listeners with the speech, which was to shorten EDT by MINT in the subjective assessments using real room impulse response.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.10-17
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• 2010

In a passive sonar, the improvement of detection performance by using noise cancellation is usually a important problem. In this paper, we have analyzed the own-ship noise cancellation in the two operation modes which are used in the HMS system. In the operator mode, an adaptive line enhancer(ALE) is applied to improve the tonal detection by using broadband noise cancellation and the normalized least mean square(NLMS) algorithm is applied to the design of an adaptive filter. The reference input that is correlated with a primary input can be used to remove the noise incident on the observation directionin the automatic mode. Computer simulations with real sea that data show that the proposed adaptive noise canceller has good performance in passive detection under HMS operation.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.280-287
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• 2016

In this paper, we propose a normalization algorithm that can be applied to adaptive filters for multi-channel active noise control. The FxLMS (Filtered-x Least Mean Square) algorithm for the single-channel active noise control can be normalized in the same way as the NLMS (Normalized Least Mean Square) algorithm, whereas in case of the multi-channel active noise control, the single-channel normalization for the FxLMS algorithm cannot be extended to the normalization for the multi-channel FxLMS algorithm straightforwardly. First, we adopt a generalized normalization algorithm for the multi-channel FxLMS algorithm based on the principle of minimal disturbance and then, proposed a normalized algorithm considering only diagonal elements to avoid computation for matrix inversion. We carried out performance comparisons of the proposed algorithm with other algorithms without normalization. It is shown that the proposed algorithm presents better convergence characteristics under non-stationary environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1650-1658
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• 1998

This paper describes how to remove echoes effectively using speech parameter information provided form speech coder. More specially, the proposed adaptive echo canceller utilizes the excitation signal or linearly predicted error signal instead of output speech signal of vocoder as the input signal for adaptation algorithm. The normalized least mean ssquare(NLMS) algorithm is used for the adaptive echo canceller. The proposed algorithm showed a fast convergece charactersitcis in the sinulatio compared to the conventional method. Specially, the proposed echo canceller utilizing the excitation signal of speech coder showed about four times fast convergence speed over the echo canceller utilizing the output speech signal of the speech coder for the adaptation input.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.9
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• pp.671-679
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• 1991

In adaptive antenna, several models are known according to a prior knowledge about jammer signal. Among those, Frost model with contraint is generally used however it has the problem that convergence speed is slow and that stability is not good. To improve such problems, this paper proposes constrained NLMS algorithm using LS method. In addition, the result obtained by applying this algorithm to Duvall antenna model is compared with that of Frost model.

• The Journal of the Acoustical Society of Korea
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• v.31 no.2
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• pp.79-86
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• 2012

In this paper, we propose an enhanced algorithm for affine projection algorithms which have been proposed to speed up the convergence of the conventional NLMS algorithm. Since affine projection (AP) or pseudo AP algorithms are based on the delayed input vector and error vector, they are complicated and not suitable for applying methods developed for the LMS-type algorithms which are based on the scalar error signal. We devised a variable step size algorithm for pseudo AP using the fact that pseudo AP algorithms are updated using the scalar error and that the error signal is getting orthogonal to the input signal. We carried out a performance comparison of the proposed algorithm with other pseudo AP algorithms using a system identification model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.9
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• pp.37-43
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• 2010

An Interference Cancellation Wireless Repeater transmitts directly amplified the RF signal input to extend the coverage of the base station. Such a repeater inevitably suffers from the feedback interferences due to the environment and the adaptive Interference Cancelling System(ICS) is necessary. In this paper, the Variable Stepsize Complex Sign -Sign(VSCSS) LMS algorithm for ICS is presented. The algorithm can be implemented without multiplication/division arithmetic operation so that the required logic resources can be dramatically reduced in FPGA implementation. The performance of the proposed algorithm was analyzed in comparison with CSS-LMS algorithm and the learning curves obtained from simulation showed an excellent agreement with the theorical prediction. The simulation result with ICS in fading feedback channel environment showed the performance of the proposed algorithm is competible with NLMS algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.163-174
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• 2009

Applying the maximally polyphase decomposition and noble identity to the adaptive filter in subband structure, the conventional fullband affine projection algorithm is translated to the subband affine projection (SAP) algorithm. The Maximally polyphase decomposed SAP (MPDSAP) algorithm is a special version of the SAP algorithm, and its adaptive sub-filters have unity projection dimension. The weight updating formular of the MPDSAP is similar to that of the NLMS algorithm, so it may be more proper algorithm than other AP-type algorithms for many practical applications. This paper presents a new statistical analysis of the MPDSAP algorithm. The analytical model is derived for autoregressive (AR) inputs and the nonunity adaptive gain in the subband structure with the orthonormal analysis filters (OAF), The pre-whitening by the OAF allows the derivation of a simple-analytical model for the MPDSAP with the AR inputs and the nonunity adaptive gain.