• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.269-274
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• 1986

A continuous-time modified gain extended Kalman filter (MGEKF) is developed in an effort to extend the discrete-time results of 1) and 2). Used as an observer, it is globally exponentially convergent. For stochastic system, the stability of the MGEKF is proven under certain conditions. The performance of the MGEKF is compared with that of the EKF for a particular nonlinear system where the fininate dimensional optimal filter exists.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.663-666
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• 2004

In this paper, a modified-SOYA (soft output viterbi algorithm) of turbo codes is proposed for quantized channel receiver filter outputs. We derive optimum branch values for the Viterbi algorithm. Here we assume that received filter outputs are quantized and the channel is additive white Gaussian noise. The optimum non-uniform quantizer is used to quantize channel receiver filter outputs. To compare the BER (bit error rate) performance we perform simulations for the modified SOYA algorithm and the general SOYA

• 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.

• ETRI Journal
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• v.35 no.5
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• pp.943-946
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• 2013

Instead of the extended Kalman filter, the unscented Kalman filter (UKF) has been used in nonlinear systems without initial accurate state estimates over the last decade because the UKF is robust against large initial estimation errors. However, in a multirate integrated system, such as an inertial navigation system (INS)/Global Positioning System (GPS) integrated navigation system, it is difficult to implement a UKF-based navigation algorithm in a low-grade or mid-grade microcontroller, owing to a large computational burden. To overcome this problem, this letter proposes a modified UKF that has a reduced computational burden based on the basic idea that the change of probability distribution for the state variables between measurement updates is small in a multirate INS/GPS integrated navigation filter. The performance of the modified UKF is verified through numerical simulations.

• Journal of Biomedical Engineering Research
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• v.11 no.1
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• pp.113-120
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• 1990

In this paper, the deconvolution method utilizing a modified Wiener filter is applied for the enhancement of lateral resolution of ultrasonic B-scan Images. For this purpose, a phantom composed of wires which are 0.6mm of diameter and apart in the range between 3 to 9mm is constructed. The modified Wiener filter with optimal parameter is applied to the phantom for the analysis of ultrasonic image. The results obtained are as follows'When all parameters of the modified Wiener filter are optimal, the resolution of B-scan images is enhanced by 50 percent : Othenrise, the images are blurred, spilt at peak points, or noises are strengthened severely. When the point-spread function representing the characteristic function of the system is determined, the selection ranges of op- timum parameters may be narrowed. It is expected that the proposed method may be able to apply to clinic situations for more accurate image analysis by means of reducing the loss of important information.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.653-658
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• 2015

This paper deals with an efficient optimization design method of a compact ultra wideband (UWB) filter which can improve the characteristics of the filter. The Evolution Strategy (ES) algorithm is adopted for the optimization and modified to suppress the ripple by inserting an additional step to the ES scheme. The algorithm has the ability to control the ripple of an insertion loss in a passband as a modified approach. During the modified ES, a structure of initial shape is changed a lot, while includes the stepped impedance (SI) and the composite right/left handed transmission line (CRLH-TL). And an optimized filter satisfies the UWB specifications on the stopband and passband with an acceptable insertion loss. The filter achieves a much developed shape, the size of $15{\times}14mm$, the 3dB bandwidth from 2.7 to 10.8GHz, the flat insertion-loss less than 1dB, the wide stopband with 12~20GHz, and an acceptable return loss.

• Smart Structures and Systems
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• v.4 no.3
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• pp.319-342
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• 2008

Identification of the nonlinear hysteretic behavior of a reinforced concrete (RC) bridge pier subjected to earthquake loads is carried out based on acceleration measurements of the earthquake motion and bridge responses. The modified Takeda model is used to describe the hysteretic behavior of the RC pier with a small number of parameters, in which the nonlinear behavior is described in logical forms rather than analytical expressions. Hence, the modified extended Kalman filter is employed to construct the state transition matrix using a finite difference scheme. The sequential modified extended Kalman filter algorithm is proposed to identify the unknown parameters and the state vector separately in two steps, so that the size of the problem for each identification procedure may be reduced and possible numerical problems may be avoided. Mode superposition with a modal sorting technique is also proposed to reduce the size of the identification problem for the nonlinear dynamic system with multi-degrees of freedom. Example analysis is carried out for a continuous bridge with a RC pier subjected to earthquake loads in the longitudinal and transverse directions.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.984-990
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• 2002

We propose a new type of nonlinear fixed interval smoother to which an existing nonlinear smoother is modified. The nonlinear smoother is derived from two-filter formulas. For the backward filter. the propagation and the update equation of error states are derived. In particular, the modified update equation of the backward filter uses the estimated error terms from the forward filter. Data fusion algorithm, which combines the forward filter result and the backward filter result, is altered into the compatible form with the new type of the backward filter. The proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing algorithm to off-line navigation system and show the proposed algorithm estimates position, and altitude fairly well through the computer simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.207-213
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• 2014

In this paper, we propose a modified median filter for impulse noise reduction. The proposed method based on multi-step finds noisy pixels from the corrupted image and applies filtering on the noisy pixels. Neighbor pixels for filtering are filtered by linear filter which adjusts filtering direction according to an edge. Thus, our proposed method not only preserves edge, but also reduces noise in uniform region. Experimental results show that our proposed method has better quality than those by existing modified median filtering method.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.159-162
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• 2008

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.