• Speech Sciences
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• v.8 no.2
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• pp.73-81
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• 2001

In this paper, we focus on the real time implementation of the single channel adaptive noise canceller(ANC) by using TMS320C30 EVM board. The implemented single channel adaptive noise canceller is based on a reference paper [1] in which it is simulated by using the recursive average magnitude difference function(AMDF) to get a properly delayed input speech on a sample basis as a reference signal and normalized least mean square(NLMS) algorithm. To certify results of the real time implementation, we measured the processing time of the ANC and enhancement ratio according to various signalto-noise ratios(SNRs). Experimental results demonstrate that the processing time of the speech signal of 32ms length with delay estimation of every 10 samples is about 26.3 ms, and almost the same performance as given in [1] is obtained with the implemented system.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.432-437
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• 1998

NLMS 알고리즘을 채용한 음향반향제거기는 주변잡음에 대해서 적응필터의 계수가 오조정되어 반향제거기의 성능이 저하된다. 본 논문에서 음향반향제거기의 마이크 입력신호와 추정 오차신호의 상관도를 이용해서 주변 잡음신호에 의한 계수 오조정이 작은 적응 알고리즘과 잔여반향을 제거하기 위한 후처리기로 구성된 음향 반향 제거기를 제안한다. 기존의 NLMS 알고리즘이 입력신호의전력으로 적응상수를 정규화하지만 제안하는 알고리즘은 마이크 입력신호와 추정 오차신호의상관도와 입력신호 전력의 합으로 정규화한다. 적응필터가 반향 경로를 추정한 경우, 추정 오차신호에는 근단화자 신호가 대부분을 차지한다. 따라서 근단화자 신호가 있는 경우에는 상관도 값이 커져서 적응 상수가 작아지고 근단화자 신호에 의한 계수의 오조정을 줄일 수 있다. 후처리기도 마이크 입력신호와 추정 오차신호의 상관도를 마이크 입력신호의 전력으로 정규화한 값으로 추정 오차신호를 감쇠시킴으로써 근단화자 신호는 감쇠를 적게 하고 잔여반향을 감쇠시킨다. 멀티미디어 PC를 이용한 실험을 통해서 제안하는 알고리즘이 기존의 알고리즘에 비해서 우수한 성능을 보임을 확인했다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.4
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• pp.484-490
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• 2012

In this paper, we design a digitally pre-distorted RF power amplifier operating in 900 MHz band. The linearity of RF power amplifier is improved by employing the digital pre-distortion(DPD) based on affine projection(AP) algorithm, where the look-up table(LUT) method is used with non-linear indexing. The proposed DPD with AP algorithm is compared with that with normalized least mean square(NLMS) algorithm, applied to the RF power amplifier. A commercial power amplifier module is used for verification of the proposed algorithm which shows improvement of adjacent channel leakage ratio(ACLR) by about 21 dB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.703-711
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• 2005

This paper proposes the improved orthogonal projection method as a new technique advancing the performance of the echo cancellation for speeches in the acoustic echo canceller. Comparing with the used NLMS adaptive algorithm, it shows that this method improves the performance of the echo cancellation for signals with the large auto-correlation. In order to testify performances of the orthogonal projection method whom this paper proposes, we have coded a simulation program and executed computer simulations. We observed convergence curves by using two adaptive algorithm for noises and speeches. From simulation results for two input signals, the proposed method shows the high ERLE and the fast convergence and the stable operation in case of using speeches as well as noises.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4
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• pp.261-268
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• 2003

Conventional acoustic echo cancellers using ES algorithm have simple structure and fast convergence speed compared with those using NLMS algorithm, but they are very weak to external noise because ES algorithm updates the adaptive filter taps based on average energy reduction rate of room impulse response in specific acoustical condition. To solve this problem, in this paper, a new update algorithm for acoustic echo canceller with stepsize matrix generator is proposed. A set of stepsizes is determined based on residual error energy which is estimated by two moving average operators, and applied to the echo canceller in matrix from, resulting in improved convergence speed. Simulations in various noise condition show that the proposed algorithm improves the robustness of acoustic echo canceller to external noise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.145-156
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• 2005

In application for acoustic echo cancellation and adaptive equalization, input signal is highly correlated and the long length of adaptive filter is needed. Affine projection algorithms, in these applications, can produce a good convergence performance. However, they have a drawback that is a complex hardware implementation. In this paper, we propose a new subband affine projection algorithm with improved convergence and reduced computational complexity. In addition, we suggest a good approach to implement the proposed method. In this method by applying polyphase decomposition, noble identity and critical decimation to the anne projection algorithm the number of input vectors for decorrelation can be reduced. The weight-updating formula of the proposed method is derived as a simple form that compared with the NLMS(normalized least mean square) algorithm by the reduced projection order The efficiency of the proposed algorithm for a colored input signal was evaluated by using computer simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1274-1285
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• 1991

This paper presents a statistical convergence analysis of the normalized least mean square(NLMS)algorithm that employs a single-pole lowpass filter, In this algorithm the lowpass filter is used to adjust its output towards the estimated value of the input signal power recursively. The estimated input signal power so obtained at each time is then used to normalize the convergence parameter. Under the assumption that the primary and reference inputs to the adaptive filter are zero mean wide sense stationary, and Gaussian random processes, and further making use of the independence assumption. we derive expressions that characterize the mean and maen squared behavior of the filter coefficients as well as the mean squared estimation error. Conditions for the mean and mean squared convergence are explored. Comparisons are also made between the performance of the NLMS algorithm and that of the popular least mean square(LMS) algorithm Finally, experimental results that show very good agreement between the analytical and emprincal results are presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.49-57
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• 1994

An efficient approach for the computationtion of the optimum convergence factor is proposed for the LMS algorithm applied to a transversal FIR structure in this study. The approach automatically leads to an optimum step size algorithm at each weight in every iteration that results in a dramatic reduction in terms of convergence time. The algorithm is evaluated in system identification application where two alternative computer simulations are considered for time-invariant and time-varying system cases. The results show that the proposed algorithm needs not appropriate convergence factor and has better performance than AGC(Automatic Gain Control) algorithm and Karni algorithm, which require the convergence factors controlled arbitrarily in computer simulation for time-invariant system and time-varying systems. Also, itis shown that the proposed algorithm has the excellent adaptability campared with NLMS(Normalized LMS) algorithm and RLS (Recursive least Square) algorithm for time-varying circumstances.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.637-645
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• 2006

An adaptive algorithm for reducing the hardware complexity is presented. This paper proposes a simplified LMS algorithm for the adaptive system and analyzes its convergence characteristics mathematically. An objective of the proposed algorithm is to reduce the hardware complexity. In order to test the performances, it is applied to the echo canceller, and a program is described. The results from simulations show that the echo canceller adopting the proposed algorithm achieves almost the same performances as one adopting the NLMS algorithm. If an echo canceller is implemented with this algorithm, its computation quantities are reduced to the half as many as the one that is implemented with the LMS algorithm, without so much degradation of performances.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.559-567
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• 2020

This paper proposes a noise cancelling algorithm to remove own-ship noise for a towed array sonar. Extra beamforming is performed using partial channels of the acoustic array to get a reference beam signal robust to the noise bearing. Frequency domain Adaptive Noise Cancelling (ANC) is applied based on Normalized Least Mean Square (NLMS) algorithm using the reference beam. The bearing of own-ship noise is estimated from the coherence between the reference beam and input beam signals. Own-ship noise level is calculated using a beampattern of the noise with estimated steering angle, which prevents loss of a target signal by determining whether to update a filter so that removed signal level does not exceed the estimated noise level. Simulation results show the proposed algorithm maintains its performance when the own-ship gets out off its bearing 40 % more than the conventional algorithm's limit and detects the target even when the frequency of the target signal is same with the frequency of the own-ship signal.