• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.911-916
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• 2010

This paper proposes a new algorithm to cancel the acoustic feedback and noise signals in digital hearing aids. The proposed algorithm combines the feedback canceller to remove acoustic feedback signals and the noise canceller to reduce background noises. The feedback canceller is implemented by normal adaptive FIR filter, and the noise canceller is implemented by using the Wiener solution in frequency domain. This noise canceller has the transfer function presented by the power spectral density of signals. To verify the performances of the proposed algorithm, the simulations were carried out for the system. As the results of simulations, it was proved that we can advance 10.85dB output SNR on the average for the forward path gain of 0dB, and 11.04dB output SNR on the average for the forward path gain of 6dB, in the case of using the proposed algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.109-112
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• 2005

ATSC 지상파 DTV 시스템에서 심볼 타이밍 동기 성능 개선을 위한 알고리즘을 제안한다. 일반적으로 심볼 타이밍 동기를 위해 사용되는 가드너 방법은 다중 경로 페이딩 환경에서 성능이 좋지만 지터에 의해 성능 열화가 발생한다. 지터량는 루프 필터 대역폭이 작을수록 작아지지만, 수렴속도는 느려지게 된다. 수렴속도는 빠르면서 수렴 후 지터량를 감소시키기 위해 일정시간마다 루프필터의 출력 값을 평균하고 이 평균값을 이용하여 옵셋량을 추정한 후 추정된 옵셋의 변화율에 따라 루프 필터의 대역폭을 줄여 지터의 크기를 줄이는 알고리즘을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.73-83
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• 2007

In this paper, we propose macroblock(MB)-based adaptive interpolation filter method for improving coding efficiency in H.264/AVC. In the proposed method, nine separable two-dimensional(2D) interpolation filters are applied for precisely compensating motions in various directions. The optimal cost function which considers the bit rate and distortion for coding the MB is defined. The filter is adaptively selected per MB for minimizing the defined cost function. In the experimental results, the proposed method shows more excellent in coding efficiency than the conventional methods for the various standard $QCIF(176{\times}144)/CIF(352{\times}288)$ video test sequences. It leads to about 6.25%(1 reference frame) and 3.46%(5 reference frames) bit rate reduction on average compared to the H.264/AVC.

• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.283-289
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• 2010

Recent advance of digital camera results in that image signal processing techniques are widely adopted to railroad security management. However, due to the nature of railroad management many images are acquired in low light level environment such as night scenes. The lack of light causes lots of noise in the image, which degrades image quality and causes errors in the next processes. 3D noise reducing techniques produce better results by using consecutive sequence of images. On the other hand, they cause degradation such as motion blur if there are motions in the sequence. In this paper, we use an adaptive weight filter to estimate more accurate motions and use the result of the adaptive filter to 3D result to improve objective and subjective mage quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.328-336
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• 2006

A novel pre-equalization method for terrestrial DTV transmitters is presented. A pre-equalizer has been used in transmitters to correct group delay and amplitude distortions caused by a channel filter. In the proposed pre-equalizer, an equation-error adaptive IIR filtering scheme is adopted unlike the conventional pre-equalization using FIR filtering schemes. The pole-zero modelling property of IIR filters improves the signal-to-noise ratio and may deal with diverse linear distortions existing in DTV transmitters as well as the channel filter distortion. Simulation results show that the proposed IIR pre-equalizer performs better than the FIR pre-equalizer in terms of the residual mean-square error.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.987-994
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• 2020

In this paper, we studied the effect of kernel size of CNN layer on performance in acoustic noise attenuators. This system uses a deep learning algorithm using a neural network adaptive prediction filter instead of using the existing adaptive filter. Speech is estimated from a single input speech signal containing noise using a 100-neuron, 16-filter CNN filter and an error back propagation algorithm. This is to use the quasi-periodic property in the voiced sound section of the voice signal. In this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed to verify the performance of the noise attenuator for the kernel size. As a result of the simulation, when the kernel size is about 16, the MSE and MAE values are the smallest, and when the size is smaller or larger than 16, the MSE and MAE values increase. It can be seen that in the case of an speech signal, the features can be best captured when the kernel size is about 16.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2
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• pp.40-49
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• 1995

Application of the filtered-x LMS adaptive filter to active noise cancellation requires to estimate the transfer charactersitics between the output and the error signal of the adaptive canceler. In this paper, we derive the filtered-x adaptive noise cancellation algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.70-76
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• 1996

In the case of an image corrupted with mixed noise, conventional MMSE filter can not remove such a mixed noise properly, because the impulse moise cause a certain bias of the minimum mean-square error estimate at regions close to outliers. In this paper, we proposed the new method or removal of mixed noise by combining MMSE filtering structure with local multi-windowing method according to directions and with ranked-order method. As a result, the improvement of the image quality with the proposed was obtained between about 9.7 and 35.2 times in the sense of NMSE(normalized mean square errors) evaluation than that of MMSE filter. Also, we could obtain the enhanced image in the mixed noisy image from visual and quantitative aspect.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4C
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• pp.312-320
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• 2008

The macroblock-based adaptive interpolation filter method has been considered to be able to achieve high coding efficiency in H.264/AVC. In this method, although the filter selection criterion considered in terms of rate and distortion have showed a good performance, it still leaves room for improvement. To improve high coding efficiency better than conventional method, we propose a new filter selection criterion which considers two bit rates, motion vector and prediction error, and reconstruction error. In addition, the algorithm for reducing the overhead of transmitting the selected filter information is presented. Experimental results show that the proposed method significantly improves the coding efficiency compared to ones using conventional criterion. It leads to about a 5.19% (1 reference frame) and 5.14% (5 reference frames) bit rate savings on average compared to H.264/AVC, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.22-33
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• 2005

In this paper, an efficient signal interference control technique to improve the high convergence speed of LMS algorithms is introduced in the adaptive transversal filter of DS/SS. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, is analyzed to prove theoretically the improvement of high convergence speed. According as the step-size parameter ${\mu}$ is increased, the rate of convergence of the algorithm is controlled. Also, an increase in the stop-size parameter ${\mu}$ has the effect of reducing the variation in the experimentally computed learning curve. Increasing the eigenvalue spread has the effect of controlling which is downed the rate of convergence of the adaptive equalizer. Increasing the steady-state value of the average squared error, proposed algorithm also demonstrate the superiority of signal interference control to the filter algorithm increasing convergence speed by (B+1) times due to the data-recycling LMS technique.