• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.548-551
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• 2003

The adaptive filter is proposed for removing EOG from measured EEG on the frontal lobe. The proposed adaptive filter has been implemented and the feedback output control algorithm has been employed to control the alpha wave ratio on the basis of TMS320C31 DSP board with the on-line and real time performance. The feedback algorithm controls the input voltage of stimulating devices on the portable bio-feedback system. The EEG data are acquired at the $F_{p1}$ and $F_{p2}$ localization and are processed by the proposed adaptive filter. We demonstrated that the proposed adaptive filter could effectively remove EOG from the measured EEG on the frontal lobe and the feedback algorithm is proper to control the output voltage of DSP board using the ratio of the alpha wave.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.145-155
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• 1990

In this paper, an adaptive Infinite Impulse Response (IIR) filter algorithm using output error method, which prevents poles of a system transfer function from being out of unit circle, is proposed, and it is proved that the proposed algorithm always satisfies hyperstability. The proposed algorithm is applied to an Adaptive Noise Canceller (ANC), and compared with a Least Square (LS) method adaptive IIR filter algorithm and an adaptive Finite Inpulse Response (FIR) filter algorithm. As a result, the validity of the proposed algorithm is proved.

• Journal of the Korea society of information convergence
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• v.5 no.2
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• pp.101-108
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• 2012

In the present paper, it removed the low frequency noise under 1Hz which get up base wandering from the various noise which is included in ECG signals. It used wavelet filter, FIR filter and Adaptive FIR filter and compared the efficiency of the filter. The set condition of 3 kind filters which are the comparative object is the next contents. Used wavelet case, used generating functions db7 and after decomposition, the low frequency of 8 phases (cA8) replaced at 0. FIR filter case, filter coefficient set 1400, cutoff frequency (${\omega}$) set 0.002. Adaptive FIR filter case, collecting coefficients (${\mu}$) with 0.005. The comparative result from the output wave shape and FT spectrum, wavelet is excellent in base wandering removals compared FIR filter and Adaptive FIR filter. And SNR comparisons, wavelet filter(44.16) is high compare with other two filters(25.19 and 15.94).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.673-677
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• 2003

In this study, we propose the new filter bank that is adaptive filter bank using neural networks in time domain. Also, we proposed a new filter neuron as neuron with filter window, the structure and algorithm for filter banks. The performance of neural filter banks is shown from two examples. It show characteristics the simple structure and higher speed processing than traditional methods (filter banks in frequency domain, etc.). In many applications, the proposed method will provide the high performance to features detection of signals in time domain.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3118-3120
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• 2000

In this paper. a stable IIR adaptive filter for active noise control is proposed. The IIR filter structure is more effective when acoustic feedback exists, in which case an order of a FIR filter must be very large if some of the poles of the ideal control filter are near the unit circle. But the IIR filter may have stability problems especially when the adaptive algorithm is not converged. A stabilizing procedure for IIR adaptive filter is presented in this paper, and computer simulation is performed to show the effectiveness of proposed schemes.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.53-59
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• 1989

A new proposed method can separate heart sounds and lung sounds by the realization of adaptive noise canceler using adaptive lattice Wiener filter in contrast to adaptive transversal LMS filter and high pass filter as before. Lung sounds and ECG signal are detected for this purpose, and especially the second heart sounds are reduced by finding T wave location with a T wave seeking algorithm. As a result, for heart sounds reduction It was found that adaptive transversal LMS filter required 100-200's orders, 75-100's orders In adaptive transversal MLMS filter, and only 10-20's orders in adaptive lattice Wiener filter. Adaptive filtering technique has shown greater accuracy than high pass filtering without loss of low frequency component.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.922-934
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• 1993

In this paper, statistical properties of the spatiotemporal center weighted median(CWM) filter for image sequences are investigated. It is statistically shown that the CWM filter preserves image structures under motion at the expense of noise suppression. To improve the CWM filter, a filter which can be effectively used in image sequence processing, the adaptive directional center weighted median filter (ADCWM), is proposed. This filter utilizes a multistage filtering structure based on adaptive symmetric order statistic(ASOS) operators which produce a pall of order statistics symmetric about the median. The ASOS's are selected by using adaptive parameters adjusted by local image statistics. It is shown experimentally that the proposed filter can preserve image structures while attenuating noise without the use of motion estimation.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.3-7
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• 2001

In active sonar system using CW signal, when the noise included reverberation has not the white characteristics, the CFAR detector estimates high threshold. Because of this reason it cannot detect targets and not resolve the closely spaced multiple targets. In order to solve these problems, we propose an adaptive reverberation rejection filter The proposed filter is composed of an adaptive filter and a fixed filter with its coefficients. To study the performance of the proposed adaptive reverberation rejection filter, various experiments have been performed under In moving active sonar environments. As a results, the proposed method has the improved performance than the previous methods.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.30-36
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• 2002

This paper describes a nonlinear adaptive noise canceler(ANC) using neural networks(NN) based on filter to make up for the drawback of the conventional ANC with the linear adaptive filter. The proposed ANC was tested its noise rejection performance using broadband time-varying noise signal and compared with the ANC of TDL linear filter. Experimental results show that in cases of nonlinear correlations between the noise of primary input and reference input, the neural network based ANC outperforms the linear ANC with respect to mean square error It is also verified that the recurrent NN adaptive filter is superior to the feedforward NN filter. Thus, we identify that the NN adaptive filter is more effective than the linear adaptive filter for rejection of broadband time-varying noise in the ANC.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.191-194
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• 2000

Frequency domain adaptive filter is effective to communication fields of many computational requirements. In this paper we propose a new variable step size algorithms which improves the convergence speed and reduces computational complexity for frequency domain adaptive filter. we compared MSE of the proposed algorithms with one of normalized FLMS using computer simulation of adaptive noise canceler based on synthesis speech.