• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.2
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• pp.63-70
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• 1996

In this paper, we propose the low sldelobe digital doppler filter bank design algorithm which is practically applicable to coherent radar equipment in complex air-defense system. Using the proposed algorithm, we can obtain a digital doppler filter bank of lower peak sidelobe level and higher clutter suppression capability. In this method, it is possible to achieve higher target-detectability without loss of Target SNR. The proposed algorithms are verified by simulations and experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.6
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• pp.49-55
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• 2004

The increase of computing power makes stochastic optimization algorithms available in structural design. One of the stochastic algorithms, simulated annealing algorithm, has been applied to various structural optimization problems. By applying several cooling schedules such as simulated annealing (SA), Boltzmann annealing (BA), fast annealing (FA) and adaptive simulated annealing (ASA), truss structures are optimized to improve the quality of objective functions and reduce the number of function evaluations. In this paper, many cooling parameters have been applied to the cooling schedule of ASA. The influence of cooling parameters is investigated to find the rules of thumb for using ASA. Tn addition, the cooling schedule combined with BA and ASA is applied to the optimization of ten bar-truss and twenty five bar-truss structure.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.9-18
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• 2010

This paper proposes a deformable registration method using a demon algorithm for aligning the lungs between end-exhale and end-inhale CT scans. The lungs are globally aligned by affine transformation and locally deformed by a demon algorithm. The use of floating gradient force allows a fast convergence in the lung regions with a weak gradient of the reference image. The active-cell-based demon algorithm helps to accelerate the registration process and reduce the probability of deformation folding because it avoids unnecessary computation of the displacement for well-matched lung regions. The performance of the proposed method was evaluated through comparisons of methods that use a reference gradient force or a combined gradient force as well as methods with and without active cells. The results show that the proposed method can accurately register lungs with large deformations and can reduce the processing time considerably.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1187-1193
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• 2011

In this paper, proposed controller preventing compressor surge and reducing the acceleration time of the fuel flow control system for turbo-jet engine. Turbo-jet engine controller is designed by applying fuzzy PID control algorithm and high-gain observer. Observer is used to estimate to compressor rotation speed of turbo-jet engine. Result of fuzzy inference is used as the fuel flow control inputs for preventing compressor surge and flame-out in turbo-jet engine. The controller is designed to converge to the desired speed quickly and safely. Using MATLAB to perform computer simulations verified the performance of the proposed controller.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.841-848
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• 2004

Evolutionary a1gorithms are well-suited for multi-objective optimization problems involving several, often conflicting objectives. Pareto-based evolutionary algorithms, in particular, have shown better performance than other multi-objective evolutionary algorithms in comparison. However, generalized evolutionary multi-objective optimization algorithms have a weak point, in which the distribution of solutions are not uni-formly distributed onto Pareto optimal front. In this paper, we propose an evolutionary a1gorithm for multi-objective optimization which uses seed individuals in order to overcome weakness of algorithms Published. Seed individual means a solution which is not located in the crowded region on Pareto front. And the idea of our algorithm uses seed individuals for reproducing individuals for next generation. Thus, proposed a1go-rithm takes advantage of local searching effect because new individuals are produced near the seed individual with high probability, and is able to produce comparatively uniform distributed pareto optimal solutions. Simulation results on five testbed problems show that the proposed algo-rithm could produce uniform distributed solutions onto pareto optimal front, and is able to show better convergence compared to NSGA-II on all testbed problems except multi-modal problem.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.977-985
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• 2009

This paper proposes a real-time algorithm for tracking the fast moving human body. Although Iterative closest point (ICP) algorithm is suitable for real-time tracking due to its efficiency and low computational complexity, ICP often fails to converge when the human body moves fast because the closest point may be mistakenly selected and trapped in a local minimum. To overcome such limitation, we combine a particle filter based on a motion history information with the ICP. The proposed human body motion tracking algorithm reduces the search space for each limb by employing a hierarchical tree structure, and enables tracking of the fast moving human bodies by using the motion prediction based on the motion history. Experimental results show that the proposed human body motion tracking provides accurate tracking performance and fast convergence rate.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.149-156
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• 2020

The genesis of ore bodies is a very diverse and complex process, and the target depth of mineral exploration increases. These create a need for predictive mineral exploration, which may be facilitated by the advancement of machine learning and geological database. In this study, we confirm that the faults and igneous rocks distributions and magnetic data can be used as input data for potential mapping using deep neural networks. When the input data are constructed with faults, igneous rocks, and magnetic data, we can build a potential mapping model of the metal deposit that has a predictive accuracy greater than 0.9. If detailed geological and geophysical data are obtained, this approach can be applied to the potential mapping on a mine scale. In addition, we confirm that the magnetic data, which provide the distribution of the underground igneous rock, can supplement the limited information from the surface igneous rock distribution. Therefore, rather than simply integrating various data sets, it will be more important to integrate information considering the geological correlation to genesis of minerals.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.562-572
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• 2003

A matched-target model inversion method was developed for a passive sonar to estimate the position of moving targets. Based on the well known matched-field processing in underwater acoustics, the method finds target position by matching the measured target directions and frequencies with the corresponding values of the proposed target model. For the efficient and accurate estimations, the parameter searching was accomplished using a hybrid optimizing method, which first starts with a global optimization such as generic algorithm or simulated annealing then applies a local optimization of a simple down hill algorithm. The suggested method was testified using simulations for three different moving scenarios. The simulation results showed that the method is robust in convergence, even under the situation of over 5 times standard deviation of Gaussian distribution of measured error, and is practical in calculation time as well.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.408-414
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• 2013

The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.52-58
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• 2013

This paper proposes an adaptive algorithm based on a method of dynamic error signal generation suitable for signal state by examining the equalizer output signal in blind equalization. In the proposed method, it estimates the error signals using single modulus and multiple modulus each effective to the early stage of equalization or steady-state, and it generates a new error signal from the two error estimates. Two equalizer structures are implemented and their performances are compared: 1-equalizer structure that generates a new error signal by combining the two error estimates weightedly and updates the equalizer using this, and 2-equalizer structure that updates two equalizers respectively depending on the weights of the two error signals. In the proposed method, as the error signals were generated optimally before and after the initial convergence respectively, it was confirmed by computer simulations that the equalizer was updated effectively.