• Honam Mathematical Journal
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• v.30 no.1
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• pp.119-126
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• 2008

The notion of uncanny filter is introduced, and related properties are investigated. Relations between uncanny filter, closed filter, and concrete filter are given. Characterizations of uncanny filter are provided. Extension property for uncanny filter is established.

• Honam Mathematical Journal
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• v.37 no.2
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• pp.221-233
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• 2015

The notion of a mighty (vague) filter in a BE-algebra is introduced, and the relation between a (vague) filter and a mighty (vague) filter are given. We investigate an equivalent condition for a (vague) filter to be mighty, and state an extension property for mighty filter. Also we define the notion of an n-fold mighty filter which is an extended notion of a mighty filter in a BE-algebra. Characterizations of an n-fold mighty filter are given. Extension property for an n-fold mighty filter are provided.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1230-1242
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• 2007

This paper describes an IIR/FIR fusion filter for a nonlinear system, and analyzes the stability of the fusion filter. The fusion filter is applied to INS/GPS integrated system, and the performance is verified by simulation and experiment. In the fusion filter, an IIR-type filter (SPKF) and FIR-type filter (MRHKF filter) are processed independently, then the two filters are merged using the mixing probability calculated using the residuals and residual covariance information of the two filters. The merits of the SPKF and the MRHKF filter are embossed and the demerits of the filters are diminished via the filter fusion. Consequently, the proposed fusion filter has robustness against to model uncertainty, temporary disturbing noise, large initial estimation error, etc. The stability of the fusion filter is verified by showing the closeness of the states of the two sub filters in the mixing/redistribution process and the upper bound of the error covariance matrices. This fusion filter is applied into INS/GPS integrated system, and important factors for filter processing are presented. The performance of the INS/GPS integrated system designed using the fusion filter is verified by simulation under various error environments and is confirmed by experiment.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.99-107
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• 2018

In this paper, we study target tracking in two dimensional space using a Extended Kalman filter(EKF), various Extended Kalman Filter and Cost-Reference Particle Filter(CRPF), which can effectively estimate the state values of nonlinear measurement equation. We introduce various Extended Kalman Filter which the Unscented Kalman Filter(UKF), the Central Difference Kalman Filter(CDKF), the Square Root Unscented Kalman Filter(SR-UKF), and the Central Difference Kalman Filter(SR-CDKF). In this study, we calculate Mean Square Error(MSE) of each filters using Monte-Carlo simulation with unknown noise statistics. Simulation results show that among the various of Extended Kalman filter, Square Root Central Difference Kalman Filter has the best results in terms of speed and performance. And, the Cost-Reference Particle Filter has an advantageous feature that it does not need to know the noise distribution differently from Extended Kalman Filter, and the simulation result shows that the excellent in term of processing speed and accuracy.

• Journal of applied mathematics & informatics
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• v.32 no.3_4
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• pp.323-330
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• 2014

The notion of transitive filters is introduced in lattice implication algebras. A necessary and sufficient condition is derived for every filter to become a transitive filter. Some sufficient conditions are also derived for a filter to become a transitive filter. The concept of absorbent filters is introduced and their properties are studied. A set of equivalent conditions is obtained for a filter to become an absorbent filter.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.99-99
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• 2000

An effect ive filter algorithm that can manage radar beam pointing efficiently is needed to track multi-target in the air. For effective beam management the filter has lobe good enough to predict future position of target and based on this filter output radar beam is control led to point toward the predicted target position in the air. In this paper, we investigate the ${\alpha}$-${\beta}$ filter known for its brief filter structure with the steady-state Kalman filter gain, the ruv filter, and the coordinate-transformed filter that can decouple the measurement noise variance.

• Bulletin of the Korean Mathematical Society
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• v.35 no.1
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• pp.53-61
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• 1998

We introduce the concepts of a positive implicative filter and an associative filter in a lattice implication algebra. We prove that (i) every positive implicative filter is an implicative filter, and (ii) every associative filter is a filter. We provide equivalent conditions for both a positive implicative filter and an associative filter.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.6
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• pp.544-552
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• 2004

This paper deals with the hybrid active filter which can reduce the 11th/13th harmonics in AC network by using the single tuned filter. Since the proposed algorithm uses the detuning compensation capability of the filter, the output voltage of the proposed active power filter is changed according to the capacitance of capacitors, magnitude of harmonic current, resonance frequency and control mode. In this paper, the control characteristics and the design of hybrid active filter is investigated. A new hybrid active filter with new algorithm, which is an active filter with single tuned filter instead of double tuned filter, is proposed.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.556-561
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• 2011

It is generally known that particle filters can produce consistent target tracking performance in comparison to the Kalman filter for non-linear and non-Gaussian systems. In this paper, I propose a Rao-Blackwellized multiple model particle filter(RBMMPF) to enhance computational efficiency of the particle filters as well as to reduce sensitivity of modeling. Despite that the Rao-Blackwellized particle filter needs less particles than general particle filter, it has a similar tracking performance with a less computational load. Comparison results for performance is listed for the using single sensor information RBMMPF and using multisensor data fusion RBMMPF.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.176-179
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• 2010

In this paper, we propose a fast implementation of Bilateral filter for tone mapping algorithm. Bilateral filter is able to preserve detail while at the same time prevent halo-ing artifacts because of improper scale selection by ensuring image smoothed that not only depend on pixel closeness, but also similarity. We accelerate Bilateral filter by using a piecewise linear approximation and recursive Gaussian filter as its domain filter. Recursive Gaussian filter is scale independent filter that combines low cost 1D filter which makes this filter much faster than conventional convolution filter and filtering in frequency domain. The experiment results show that proposed method is simpler and faster than previous method without mortgaging the quality.