• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.10-18
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• 2000

This paper proposes a fuzzy logic cross-coupled controller using a new contouring modeling for a two-axis servo system. The general decoupled control approach may result in degraded contouring performance due to such factors as mismatch of axial dynamics and axial loop gains. In practice, such systems contain many uncertainties. The cross-coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However, the conventional cross-coupled controllers cannot overcome friction, backlash, and parameter variations. Also since, it is difficult to obtain an accurate mathematical model of multi-axis system, here we investigate a fuzzy logic cross-coupled controller of servo system. In addition, new contouring error vector computation method is presented. The experimental results are presented to illustrate the performance of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.610-616
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• 2010

This paper describes how to securely bind the identity reference and biometric reference for satisfying security requirements. To overcome the shortcomings of the simple personal authentication method using a password, such as identify theft, a biometric system that utilizes physical and behavioral characteristics of each person has been adopted. In the biometric system, the biometric information itself is personal information, and it can be used as an unique identifier that can identify a particular it vidual when combining with other identity information. As a result, a son, anb it canmethod is required for manipulat canthese information. Consider canthese issues, this paper proposes a biit canmethod uiter son, anand uisecure channels for generating the common identifier and ensuring security of identity reference and biometric reference that are stored in the separated DBs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2C
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• pp.86-92
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• 2011

This paper details the downlink performance analysis of an multiple antennas system that combines adaptive beamforming and spatial multiplexing (SM) Multiple Input Multiple Output (MIMO). The combination of MIMO signal processing with adaptive beamforming is applied to WiBro, the South Korean Orthogonal Frequency Division Multiple Access (OFDMA) system that follows the IEEE 802.16e standard. Performance analysis is based on the results of experiments and simulations obtained from a fixed-point simulation testbed. Simulations demonstrate that the MIMO Beamforming OFDMA system improves the required signal to noise ratio (SNR) over the conventional MIMO OFDMA system by 3 dB (QPSK) / 2.5 dB (16-QAM) for the frame error rate (FER) of 1% in the WiBro signal environments. From the implementation of the fixed-point simulation testbed and its experimental results, we verify the feasibility of the MIMO Beamforming technology for realizing a practical WiBro base station.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.83-88
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• 2013

Many studies adopting brain functions to the engineering systems have been made for recent years as the brain Science has developed. If we investigate the parts which take part in memorizing and emotional process, we can know that Hippocampus of memorizing center and Amygdala of Emotional center closely cooperate each other. Actually Knowledge effects on Emotion and Emotion effects on Knowledge. During the human decision making, emotional factor has much important effects on Decision making process. For implementing more delicate intelligent system, the knowledge base coupled to emotional factor should be designed. Accordingly in this paper starting from the idea of cooperating system between Hippocampus and Amygdala,, we design Knowledge Emotion Binding System and propose Emotional changing mechanism by Memory retrieval and knowledge reasoning process.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.267-275
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• 2013

EKF has been widely used for GPS/INS integration as standard method but EKF has one well-known drawback. if the errors are not within the bounded region, the filter may be divergent. The particle filter has the advantage of the nonlinear and non-gaussian system. This paper proposes a method for compensating the GPS position errors based on the particle filter and presents loosely-coupled GPS/INS integration using proposed algorithm. We used GPS position pattern with particle filter and added attitude kalman filter for improving attitude accuracy. To verify the performance, the proposed method is compared with high cost GPS as reference. In the experimental result, we verified that the accuracy and robust were well improved by the proposed method filter effectively and robustness than by original loosely-coupled integration when vehicle turns at corner.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1626-1634
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• 1993

In this paper we propose a coding scheme which combines source codes and error correcting codes in order to be robus to channel noise. One of the coding schemes that take into account both the source and the channel is the channel optimized quantizer (COQ) which simultaneously minimizes quantization noise and the noise due to channel errors. This paper deals with the problem of combining channel optimized quantizers with ECC to build an improved system. To be specific, we computed the performance of an n bit COQ and that of an n-1 bit COQ followed by an (n-1)/n punctured convolutional code. From this result whether or not the ECC are selected is determined by the number of allocated bits and the channel bit error rate. These results are applied to the image trans-mission method using DCT, and the system performances are evaluated.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.396-401
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• 2006

It is well-known that a neural network with cyclic connections generates plural limit cycles, thus, being used as a memory system for storing large number of dynamic information. In this paper, a continuous-time cyclic connection neural network was built so that each neuron is connected only to its nearest neurons with binary synaptic weights of ${\pm}1$. The type and the number of limit cycles generated by such network has also been demonstrated through simulation. In particular, the effect of chaos signal for transition between limit cycles has been tested. Furthermore, it is evaluated whether the chaotic noise is more effective than random noise in the process of the dynamical neural networks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.115-127
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• 2006

The purpose of this paper is evaluation of various normalization methods and fusion algorithms in addition to pattern classification algorithms for multi-biometric systems. Experiments are performed using various normalization functions, fusion algorithms and pattern classification algorithms based on Biometric Scores Set-Releasel(BSSR1) provided by NIST. The performance results are presented by Half Total Error Rate (WTER). This study gives base data for the study on performance enhancement of multiple-biometric system by showing performance results using single database and metrics.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.63-68
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• 2020

This paper proposes a face authentication system based on deep learning framework. The proposed system is consisted of face region detection and feature extraction using deep learning algorithm, and performed the face authentication using joint-bayesian matrix learning algorithm. The performance of proposed paper is evaluated by various face database , and the face image of one person consists of 2 images. The face authentication algorithm was performed by measuring similarity by applying 2048 dimension characteristic and combined Bayesian algorithm through Deep Neural network and calculating the same error rate that failed face certification. The result of proposed paper shows that the proposed system using deep learning and joint bayesian algorithms showed the equal error rate of 1.2%, and have a good performance compared to previous approach.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.6
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• pp.846-851
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• 2010

A liquid-air interface sensing system using the flat end surfaces of a fused-silica fiber coupler has been demonstrated. The principle is based on the additional optical loss caused by changing the refractive index of the external material at the boundary of the end face made of a fiber. The immersion characteristics of this system with respect to the different splitting ratios of the couplers were investigated to determine the sensitivity when it responses to water and air. These experimental data are very useful for selecting the coupling ratio of a coupler in order to develop a multiple sensing probe system. In the proposed sensor structure, it can be emphasize that the sensing probe can be appropriately arrayed on the basis of splitting ratio of the coupler. As a result, it is expected that the proposed liquid-air interface sensors can also be applied to monitor flooding that occurs in multiple areas at the same time.