• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1016-1026
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• 2017

An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2080-2085
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• 2018

There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.9
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• pp.764-774
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• 1990

In this paper, make a study on comparison of adaptive filters for predictor characteristics that transversal, lattice, and joint process lattice filter is using the LMS algorithm that is simple structure and pracotical application is easy. The theoical background and structure of each adaptive filters exhibit for practical design. Adaptive convergence condition for optimal weight vector and optimal reflection coefficient make clear, and it is also shown through computer simulation. The error signals and noise characteristics of these filters make a comparative study. In view of the results, joint process lattice filter is shown that most superior characteristic in these adaptie filters.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.165-174
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• 2010

The H.264/AVC standard obtained better performance than previous compression standards, but it also increased the computational complexity of CODEC simultaneously. Various techniques recently included at the KTA software developed by VCEG also were increasing its complexity. Especially adaptive interpolation filter has more complexity than two times due to development for coding efficiency. In this paper, we propose low-complexity filter bank to improve speed up of decoding and coding gain. We consists of filter bank of a fixed-simple filter for low-complexity and adaptive interpolation filter for high coding efficiency. Then we compensated using optimal filter at each macroblock-level or frame-level. Experimental results shows a similar coding efficiency compared to existing adaptive interpolation filter and decoding speed of approximately 12% of the entire decoder gained.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.46-50
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• 2001

Adaptive signal processing is used to acoustic echo canceller. adaptive noise canceller and adaptive algorithm among adaptive algorithms is mainly used because the structure is simple and computa LMS algorithm has trade-off between the converge speed and the steady state error. In this paper, step-size of adaptive algorithm is varied with orthogonality Principles of optimal filter to get fasts though small steady state error. Time varying step-size is determined proportional to the maximum vector of LMS algorithm. As results of simulations, the adaptive algorithm with proposed time-v compared with conventional ones.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.287-297
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• 2018

To improve the performance of sensorless induction motor (IM) drives, a novel speed estimation method based on the real-time adaptive extended Kalman filter (RAEKF) is proposed in this paper. In this algorithm, the fuzzy factor is introduced to tune the measurement covariance matrix online by the degree of mismatch between the actual innovation and the theoretical. Simultaneously, the fuzzy factor can be continuously self-tuned tuned by the fuzzy logic reasoning system based on Takagi-Sugeno (T-S) model. Therefore, the proposed method improves the model adaptability to the actual systems and the environmental variations, and reduces the speed estimation error. Furthermore, a simple exponential function based on the fuzzy theory is used to reduce the computational burden, and the real-time performance of the system is improved. The correctness and the effectiveness of the proposed method are verified by the simulation and experimental results.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.163-174
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• 2009

Applying the maximally polyphase decomposition and noble identity to the adaptive filter in subband structure, the conventional fullband affine projection algorithm is translated to the subband affine projection (SAP) algorithm. The Maximally polyphase decomposed SAP (MPDSAP) algorithm is a special version of the SAP algorithm, and its adaptive sub-filters have unity projection dimension. The weight updating formular of the MPDSAP is similar to that of the NLMS algorithm, so it may be more proper algorithm than other AP-type algorithms for many practical applications. This paper presents a new statistical analysis of the MPDSAP algorithm. The analytical model is derived for autoregressive (AR) inputs and the nonunity adaptive gain in the subband structure with the orthonormal analysis filters (OAF), The pre-whitening by the OAF allows the derivation of a simple-analytical model for the MPDSAP with the AR inputs and the nonunity adaptive gain.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.418-428
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• 2002

In this paper, we propose a motion-adaptive de-interlacing method using motion compensated interpolation. In a conventional motion compensated method, a simple pre-filter such as line averaging is applied to interpolate missing lines before the motion estimation. However, this method causes interpolation error because of inaccurate motion estimation and compensation. In the proposed method, EBMF(Edge Based Median Filter) as a pre-filter is applied, and new matching method, which uses two same-parity fields and opposite-parity field as references, is proposed. For further improvement, motion correction filter is proposed to reduce the interpolation error caused by incorrect motion. Simulation results show that the proposed method provides better performance than existing methods.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.223-232
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• 2005

In this paper, we propose a novel post-filtering algorithm with low computational complexity that improves the visual quality of decoded images using block boundary classification and simple adaptive filter (SAF). At first, each block boundary is classified into smooth or complex sub-region. And for smooth-smooth sub-regions, the existence of blocking artifacts is determined using blocky strength. And simple adaptive filtering is processed in each block boundary area. The proposed method processes adaptively, that is, a nonlinear 1-D 8-tap filter is applied to smooth-smooth sub-regions with blocking artifacts, and for smooth-complex or complex-smooth sub-regions, a nonlinear 1-D variant filter is applied to block boundary pixels so as to reduce the blocking and ringing artifacts. And for complex-complex sub-regions, a nonlinear 1-D 2-tap filter is only applied to adjust two block boundary pixels so as to preserve the image details. Experimental results show that the proposed algorithm produced better results than those of conventional algorithms both subjective and objective viewpoints.