• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.12
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• pp.1744-1749
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• 2013

Acoustic feedback is perceived as whistling or howling, which is a major complaint of hearing-aids users. Acoustic feedback cancellation is important in hearing-aids because acoustic feedback degrades performance of the hearing aid device by reducing maximum insertion gain. Adaptive systems for estimate acoustic feedback path and feedback suppression algorithms have been proposed in order to solve this problem. A typical feedback cancellation algorithm is LMS(least mean squares) because of its computational efficiency. However it has problem of convergence performance in high correlated input signal. In this paper, we propose a new variable step-size normalized LMS(least mean squares) algorithm using VAD(voice activity detection) to overcome the limitation of the LMS algorithm. The VAD algorithm is GSAP(global speech absence probability) and the feedback cancellation algorithm is normalized LMS. The proposed algorithm applies different step-size between voice and non-voice using VAD, for high stability, fast convergence speed and low misalignment when correlated inputs, such as speech. The result of simulation with white noise mixed speech signal, the proposed algorithm shows high performance then traditional algorithm in terms of stability, convergence speed and misalignment.

• Journal of IKEEE
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• v.15 no.4
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• pp.293-298
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• 2011

In the paper, we propose a new CMF(Constant Modulus Fourth) algorithm for WCDMA(Wideband Code Multiple Access) RF(Radio Frequency) Repeater. CMF algorithm is proposed by modifying the CMA(Constant Modulus Algorithm) algorithm and improved performances are achieved by properly adjusting step size values. The steady state MSE(Mean Square Error) performance of the proposed CMF algorithm with step size of 0.35 is about 4dB better than that of the conventional CMA algorithm. And the proposed CMF algorithm requires 400~1100 less iterations than the LMS(Least Mean Square) and NLMS(Normalized Least Mean Square) algorithms at MSE of -25dB.

• 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 the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.333-337
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• 2004

This paper describe a design of 5GHz OFDM baseband chip for IEEE 802.11a wireless LAN. The proposed device is consists of transmitter and receiver within a single FPGA chip. We applied single tap equalizer that use Normalized LMS algorithm to remove ISI that happen at high speed data transmission. And also, we used carrier wave frequency offset algorithm that use training symbol to remove ICI. The simulation results show the correct transmission without errors the between transmitter and receiver And we can remarkably reduce the number of register through the synthesized circuits by using DSP block and EMB(Embedded Memory Block). The target device for implementation of the synthesized circuits is Altera Stratix EPIS25FC672 FPGA and design platform is VHDL.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.46-53
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• 1996

Adaptive LMS algorithm has been used in many application areas due to its low complexity. In this paper input signal is transformed into the subbands with arbitrary bandwidth. In each subbands the dynamic range can be reduced, so that the independent filtering in each subbands has faster convergence rate than the full band system. The DCT transform domain LMS adaptive filtering has the whitening effect of input signal at each bands. This leads the convergence rate to very high speed owing to the decrease of eigen value spread Finally, the filtered signals in each subbands are synthesized for the output signal to have full frequency components. In this procedure wavelet filter bank guarantees the perfect reconstruction of signal without any interspectra interference. In simulation for the case of speech signal added additive white gaussian noise, the suggested algorithm shows better performance than that of conventional NLMS algorithm at high SNR.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.343-348
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• 2011

This paper introduces a design for real time wireless headset using ANC (active noise control) system based on NFxLMS adaptive filter algorithm. The training time of the proposed system is significantly reduced by using the RMS delay spread of a channel as an error correction parameter, and convergence rate of the FxLMS filter has been improved with updating the coefficients of the NFxLMS filter, which we have got during the training process. Our system has shorter training time and better convergence rate at the same noise reduction level than the conventional system under real noisy environment.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.553-556
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• 2000

This paper proposes an adaptive linearization method of Volterra nonlinear systems using DWT(Discrete Wavelet Transform)and an LMS-type predistorter. In particular, the proposed wavelet transform-domain lineatization method leads to diagonalization of the input vector auto-correlation matrix which yields improvement of the convergence rate of the corresponding transform-domain LMS algorithm. Furthermore, the adaptive Volterra predistorter followed by a corresponding weakly Volterra nonlinear system(here. a TWT amplifier model in a satellite communication system) is utilized to compensate for the distortion in the output. Also,12-PSK and 4-QAM are applied as the input to the nonlinear system to be tested. Some simulation results show that the proposed linearization approach has better performance than DCT-based or conventional normalized LMS algorithms do.

• 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.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2995-2997
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• 2005

통신망에서 최적 적응 반향제거기(Echo Canceller; EC)는 반향성분이 길게 존재하는 환경에서도 실시간으로 동작할 수 있도록 알고리즘이 간결하여야 하며, 시간에 따라 빠르게 변하는 동특성의 반향경로에서도 동작을 보장할 수 있도록 빠른 수렴특성을 갖아야 한다. 또한, 전화망에서 수십 [ms] 이상의 지연이 발생 할 경우에도 반향제거 성능이 우수해야 한다. 본 논문에서는 이러한 조건을 만족시키기 위해 오차의 크기에 따라 수렴속도를 가변시키는 오차적응 NLMS(Error-Adaptive NLMS) 알고리즘을 제안하였으며, 시뮬레이션을 통해 일반적으로 사용되는 LMS(Least Mean Square) 알고리즘과 이를 개선한 NLMS(Normalized LMS) 알고리즘과 성능을 비교하였다.