• 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 Korean Institute of Telematics and Electronics
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• v.22 no.6
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• pp.76-82
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• 1985

The convergence properties of Burg algorithm, which is commonly used to calculate the reflection coefficients in the adaptive lattice filters, are studied in this paper. Applying the $\mu$ algorithm to Burg algorithm, a new adaptive lattice $\mu$ algorithm is derived and it shows that the convergence speed of this algorithm is higher than that of Burg algorithm. As a result of theoretical analysis and computer simulation, it is proved that the con-vergence speed of the proposed algorithm is remarkably higher than that of Burg algorithm when the convergence speed of Burg alsorithm is low.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.265-270
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• 2006

Recently, inertial sensors like gyros and accelerometers have been quite miniaturized by Micro Electro-Mechanical Systems (MEMS) technology. JAXA is developing a MEM-based GPS/INS hybrid navigation system named Micro-GAIA. The navigation performance of Micro-GAIA was evaluated through off-line analysis by using flight test data. The estimation errors of the roll, pitch, and azimuth were $0.03^{\circ}$, $0.05^{\circ}$, $0.05^{\circ}$ $(1{\sigma})$, respectively. he horizontal position errors after 60-second GPS outages were reduced to 25 m CEP. The attitude errors and position errors are nearly half of ones reported previously[2]. Furthermore, using the adaptive Kalman filters, the robustness against the uncertainty of the measurement noise was improved. Comparing the innovation-based and residual-based adaptive Kalman filters, it was confirmed that the latter is robuster than the former.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.5
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• pp.307-314
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• 2021

Even though the LCL filters have superior harmonic attenuation ability to L filters, stability has always been an issue. The system could be unstable because of the resonance phenomenon, especially when digital controller is used. Adding a notch filter to the compensator is one approach to solve the problem. Resonance phenomenon can be inhibited by aligning notch frequency to system resonance frequency. However, resonance frequency variation can be obtained because the actual system has a nonstationary characteristic. Therefore, the system could be unstable, where the system parameters are changed when the conventional notch filter is used. An adaptive digital notch filter that stabilizes the system even system parameters are changed. Simulation and experiment results are provided to verify the validity of the proposed adaptive filter.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.49-56
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• 1995

This paper is a study on the design of adptive filter for QRS complex detection. We propose a simple adaptive algorithm to increase capability of noise cancelation in QRS complex detection with two stage adaptive filter. At the first stage, background noise is removed and at the next stage, only spectrum of QRS complex components is passed. Two adaptive filters can afford to keep track of the changes of both noise and QRS complex. Each adaptive filter consists of prediction error filter and FIR filter. The impulse response of FIR filter uses coefficients of prediction error filter. The detection rates for 105 and 108 of MIT/BIH data base were 99.3% and 97.4% respectively.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.83-88
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• 1989

This paper is a study on the design of adptive filter for QRS complex detection. We propose a simple adaptive algorithm to increase capability of noise cancelation in QRS complex detection with two stage adaptive filter. At the first stage, background noise is removed and at the next stage, only spectrum of QRS complex components is passed. Two adaptive filters can afford to keep track of the changes of both noise and QRS complex. Each adaptive filter consists of prediction error filter and FIR filter The impulse response of FIR filter uses coefficients of prediction error filter. The detection rates for 105 and 108 of MIT/BIH data base were 99.3% and 97.4% respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2928-2947
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• 2015

Adaptive Gaussian filter (AGF) is a recently developed switching filter to remove salt and pepper noise. AGF first directly identifies pixels of gray levels 0 and 255 as noise pixels, and then only restored noise pixels using a Gaussian filter with adaptive variance based on the estimated noise density. AGF usually achieves better denoising effect in comparison with other filters. However, AGF still fails to obtain good denoising effect on images with noise-free pixels of gray levels 0 and 255, due to its severe false alarm in its noise detection stage. To alleviate this issue, a modified version of AGF is proposed in this paper. Specifically, the proposed filter first performs noise detection via an image block based noise density estimation and sequential noise density guided rectification on the noise detection result of AGF. Then, a modified Gaussian filter with adaptive variance and window size is used to restore the detected noise pixels. The proposed filter has been extensively evaluated on two representative grayscale images and the Berkeley image dataset BSDS300 with 300 images. Experimental results showed that the proposed filter achieved better denoising effect over the state-of-the-art filters, especially on images with noise-free pixels of gray levels 0 and 255.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4549-4566
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• 2017

This work presents a novel facial descriptor, which is named as multiscale adaptive local directional texture pattern (MALDTP) and employed for expression recognition. We apply an adaptive threshold value to encode facial image in different scales, and concatenate a series of histograms based on the MALDTP to generate facial descriptor in term of Gabor filters. In addition, some dedicated experiments were conducted to evaluate the performance of the MALDTP method in a person-independent way. The experimental results demonstrate that our proposed method achieves higher recognition rate than local directional texture pattern (LDTP). Moreover, the MALDTP method has lower computational complexity, fewer storage space and higher classification accuracy than local Gabor binary pattern histogram sequence (LGBPHS) method. In a nutshell, the proposed MALDTP method can not only avoid choosing the threshold by experience but also contain much more structural and contrast information of facial image than LDTP.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.151-165
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• 2010

Images are often corrupted by impulse noise due to a noise sensor or channel transmission errors. The filter based on SVM(Support Vector Machine) and the improved adaptive median filtering is proposed to preserve image details while suppressing impulse noise for image restoration. Our approach uses an SVM impulse detector to judge whether the input pixel is noise. If a pixel is detected as a noisy pixel, the improved adaptive median filter is used to replace it. To demonstrate the performance of the proposed filter, extensive simulation experiments have been conducted under both salt-and-pepper and random-valued impulse noise models to compare our method with many other well known filters in the qualitative measure and quantitative measures such as PSNR and MAE. Experimental results indicate that the proposed filter performs significantly better than many other existing filters.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.17-19
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• 2005

In this paper, using B-splines as universial approximators, we have obtained a plant parametrization which permits the construction of an adaptive observer. The particular property of this parametrization is that the dynamic order of the filters in this design does not depend on the number of parameters in the plant parametrization. This appears to be a beneficial property especially because the number of such parameters tends to be very high for universial approximator based designs.