• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11C
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• pp.1127-1133
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• 2007

This paper proposes one of normalized QR-typed LMS (Least Mean Square) algorithms with computational complexity of O(N). This proposed algorithm shows the normalized property in terms of theoretical characteristics. This proposed algorithm is one of algorithms which normalize variance of input signal in terms of mean because QR-typed LMS is proportional to variance of input signal. In this paper, convergence characteristic analysis of normalized algorithm was made. Computer simulation was made by the algorithms used for echo canceller. Proposed algorithm has similar performance to theoretical value. And, we can see that proposed method shows similar one to performance of NLMS.by comparison among different algorithms.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.42-46
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• 2002

In this paper, a new pre-processing algorithm is proposed to improve the performance of stereo acoustic echo canceller. The proposed algorithm has the improved performance by the estimation error reduction of filter coefficient using input signal which was reduced reverberation of room in the basis MINT (Mu1tip1e-input/output Inverse Theorem) filtering. For real stereo speech signal and real room impulse response the results of simulation, we showed that the proposed method could improved 3∼5 dB ERLE (Echo Return Loss Enhancement) regardless of NLMS (Normalized Least Mean Square) and Projection adaptive algorithm.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.89-95
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• 2006

The performance of blind source separation(BSS) using independent component analysis (ICA) declines significantly in a reverberant environment. A post-processing method proposed in this paper was designed to remove the residual component precisely. The proposed method used modified NLMS(normalized least mean square) filter in frequency domain, to estimate cross-talk path that causes residual cross-talk components. Residual cross-talk components in one channel is correspond to direct components in another channel. Therefore, we can estimate cross-talk path using another channel input signals from adaptive filter. Step size is normalized by input signal power in conventional NLMS filter, but it is normalized by sum of input signal power and error signal power in modified NLMS filter. By using this method, we can prevent misadjustment of filter weights. The estimated residual cross-talk components are subtracted by non-stationary spectral subtraction. The computer simulation results using speech signals show that the proposed method improves the noise reduction ratio(NRR) by approximately 3dB on conventional FDICA.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.3
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• pp.1-8
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• 2001

In the DS/CDMA mobile communication systems, the parallel interference canceller is used in order to reduce the multiple access interference and the multipath fading. It is needed the accurate interference estimate in the multistage parallel cancellation. In this paper, the adaptive cancellation method and the new tentative decision device arc proposed and the performance is analyzed. The adaptive cancellation method uses the normalized least mean square(NLMS) algorithm to calculate the weight adaptively, and new tentative decision device uses the hyperbolic tangent decision with null zone. Computer simulation shows that the proposed scheme has the improved performance and the number of user is increased 48% compared with the conventional receiver.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.54-62
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• 2000

Adaptive filtering method is one of signal processing area which is frequently used in the case of statistical characteristic change in time-varing situation. The performance of adaptive filter is usually evaluated with complexity of its structure, convergence speed and misadjustment. The structure of adaptive filter must be simple and its speed of adaptation must be fast for real-time implementation. In this paper, we propose chirp discrete cosine transform (CDCT), which has the characteristics of CZT (chrip z-transform) and DCT (discrete cosine transform), and then CDCTLMS (chirp discrete cosine transform LMS) using the above mentioned algorithm for the improvement of its speed of adaptation. Using loaming curve, we prove that the proposed method is superior to the conventional US (normalized LMS) algorithm and DCTLMS (discrete cosine transform LMS) algorithm. Also, we show the real application for the ultrasonic signal processing.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.272-279
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• 2016

In this paper, the realization of a hearing aid adaptively cancelling feedback noise was considered. Conventional least mean square method in time domain was transformed into frequency domain in order to minimize computational burden. The adaptive filter algorithm was evaluated by Matlab (Matrix laboratory), and it was confirmed by CSR 8675 Bluetooth DSP IC (Digital Signal Processor Integrated Circuit) chip firmware realization. Some remote control features by a smart phone was added to the smart hearing aid for user interface easiness.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.9-22
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• 2019

In this paper, we propose a method that can be applied to the efficient implementation of multi-channel active noise controller. Since the normalized MFxLMS (Modified Filtered-x Least Mean Square) algorithm for the multi-channel active noise control requires a large amount of computation, the difficulty has lied in implementing the algorithm using a low-cost MCU (Microcontoller Unit). We implement the multi-channel active noise controller efficiently by optimizing the software based on the features of the MCU. By maximizing the usage of single-cycle MAC (Multiply- Accumulate) operations and minimizing move operations of the delay memory, we can achieve more than 3 times the performance in the aspect of computational optimization, and by parellel processing using the auxillary processor included in the MCU, we can also obtain more than 4 times the performance. In addition, the usage of additional parts can be minimized by maximizing the usage of the peripherals embedded in the MCU.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.33-41
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• 1994

A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8C
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• pp.801-805
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• 2006

A normalization approach to coefficient adaptation in the escalator(ESC) filter structure that conventionally employs least mean square(LMS) algorithm is introduced. Using Taylor's expansion of the local error signal, a normalized form of the ESC-LMS algorithm is derived. Compared with the computational complexity of the conventional ESC-LMS algorithm employs input power estimation for time-varying convergence coefficient using a single-pole low-pass filter, the computational complexity of the proposed method can be reduced by 50% without performance degradation.