• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1092-1099
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• 2000

An adaptive array system can effectively remove all received interferences by using adaptive algorithms even though the received signal condition is not known. The conventional adaptive array systems, however, cannot remove all interferences adaptively and converge very slowly when the eigenvalue spread of the input covariance matrix is large. In the paper, a new adaptive array system called an automatic gain controller (AGC) Applebaum array and its control algorithm are proposed to overcome the performance degradation of conventional Applebaum array in multiple interference conditions. The performance analysis of the proposed AGC Applebaum array is described under the condition of multiple narrowband interferences. Simulation results show the array output signal-to-noise ratio (SNR) of the AGC Applebaum array increases by 30dB compared to that of the conventional Applebaum array in the simulation condition. The gain of the AGC Applebaum array in the incident direction of a weaker interference is also shown to be lower than that of the conventional Applebaum array.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.2
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• pp.1-8
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• 1992

This paper is proposed a Modified WLD (Weighted Levenshtein Distance) algorithm for processor desihn of code-string matching. A proposed MWLD (Modified Weighted Levenshtein Distance) algorithm is consist of 1-dimension bit-serial array processor to pattern matching using a Hamming Distance. The proposed processor is applied to recognition of character with real time input. The recognition rate of Hangul strokes is resulted to 98.65$\%$

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.545-548
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• 2000

Adaptive array systems are hard to remove all the interferences when incident signals are coherent with a desired signal. In this paper, we propose a modified Duvall beamformer, which performs spatial smoothing using spatial interpolation technique to maintain the degree of freedom. The propose algorithm can minimize the loss on the degree of freedom due to spatial smoothing by forming subarrays with interpolated signals. Simulation results show that the proposed algorithm can remove all the interferences while conventional beamformer cannot.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.63-68
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• 2000

In this paper, a control algorithm suitable for multi-objective control problems is proposed based on the orthogonal array which is normally used in statistics and industrial engineering. And a newly defined Nth-certainty factor is suggested, which can effectively exclude the less confident rules. The Nth-certainty factor is defined by the F-values of the ANOVA(analysis of variance) table. It is shown that the algorithm can be successfully adopted to the design of controller for an active magnetic bearing system.

• ETRI Journal
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• v.31 no.2
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• pp.240-242
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• 2009

A computationally efficient implementation of the progressive edge-growth algorithm is presented. This implementation uses an array of red-black (RB) trees to manage the layered structure of check nodes and adopts a new strategy to expand the Tanner graph. The complexity analysis and the simulation results show that the proposed approach reduces the computational effort effectively. In constructing a low-density parity check code with a length of $10^4$, the RB-tree-array-based implementation takes no more 10% of the time required by the original method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.8
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• pp.676-683
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• 2016

In this paper, an adaptive nulling algorithm which can be used to form nulls in the direction of jammer or interference signals in array antennas of single port system is proposed. The proposed adaptive algorithm does not require a priori knowledge of the incoming signal direction and can be applied to the partially adaptive arrays. This algorithm is the combination of the PSO(Particle Swam Optimization) algorithm and the gradient-based perturbation adaptive algorithm, which shows stable nulling performance adaptively even on the moving jammer environment where the incident direction of the interference signal is changing with time.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.299-304
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• 2018

An improved genetic algorithm was proposed for pattern synthesis of an adaptive beam forming system using phased array antennas. The proposed genetic algorithm is an algorithm that adds acquired characteristics procedure to solve local optimization using the diversity. The performance of the proposed genetic algorithm is verified through the problem of finding a suitable chromosome for a picture composed of binary. And it is confirmed that it is suitable for the adaptive beam forming system based on the performance problem of combining main beam and two pattern nulls.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.75-81
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• 2010

Adaptive array antenna system estimates target signal, as making a null pattern toward the interference signal. However, receiving a coherent interference signal at adaptive array antenna system, as target signal is regarded as interference signal, the performance of system rapidly decreases. The main beam does not direct an incidence direction of target signal due to sensitivity in directivity error. This paper proposes beamforming algorithm which combines high order limit condition and directivity error modify method. And it minimizes degree of freedom and decreases interference signal and directivity error using proposed algorithm. This paper compares and analyzes the performance of proposed algorithm and general algorithm using simulation. In this paper, the proposed algorithm correctly estimates an incident angle, but general algorithm occurs an error of about $0.8^{\circ}$.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.2
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• pp.7-16
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• 2019

Neural networks can be implemented in variety of ways, and specialized chips is being developed for hardware improvement. In order to apply such neural networks to wearable devices, the compactness and the low power operation are essential. In this point of view, a suitable implementation method is a digital circuit design using field programmable gate array (FPGA). To implement this system, the learning algorithm which takes up a large part in neural networks must be implemented within FPGA for better performance. In this paper, a back propagation algorithm among various learning algorithms is implemented using FPGA, and this neural network is verified by OR gate operation. In addition, it is confirmed that this neural network can be used to analyze various users' bio signal measurement results by learning algorithm.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.2
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• pp.114-121
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• 2009

Ultrasonic guided waves have been widely utilized for long range inspection of structures. Especially, development of array guided waves techniques and its application for long range gas pipe lines(length of from hundreds meters to few km) were getting increased. In this study, focusing algorithm for array guided waves was developed in order to improve long range inspectability and accuracy of the array guided waves techniques for long range inspection of gas pipes, and performance of the developed techniques was verified by experiments using the developed array guided wave system. As a result, S/N ratio of array guided wave signals obtained with the focusing algorithm was increased higher than that of signals without focusing algorithm.