• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.15-18
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• 2007

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e. both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion is considered at decision level. The proposed algorithm is tested on the NLPR database.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2929-2931
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• 1999

In this paper, an adaptive fuzzy inference and HCM(Hard C-Means) clustering method are used for on-line fuzzy modeling of nonlinear and complex system. Here HCM clustering method is utilized for determining the initial parameter of membership function of fuzzy premise rules and also avoiding overflow phenomenon during the identification of consequence parameters. To obtain the on-line model structure of fuzzy systems. we use the recursive least square method for the consequent parameter identification. And the proposed on-line identification algorithm is carried out and is evaluated for sewage treatment process system.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.123-128
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• 1998

This paper presents time domain identification of an interval system. We conjectured that Markov parameters (Pulse Responses) from Kharitonov plants would envelope those of the whole interval system. The examination on interrelations between Markov parameters from Kharitonov plants of an interval system and those of the whole interval system determines the validity of the conjecture and is used to give some extremal properties of Markov parameters. The results of this paper are shown in simulations on MBC500 Magnetic Bearing System and a given interval system.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1292-1298
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• 2017

In this paper, we represent a nonlinear identification of electronic brake pedal behavior in the brake-by-wire (BBW) system based on hybrid group method of data handling (GMDH) and genetic algorithm (GA). A GMDH is a kind of multi-layer network with a structure that is determined through training and which can express nonlinear dynamics as a mathematical model. The GA is used in the GMDH, enabling each neuron to search for its optimal set of connections with the preceding layer. The results obtained with this hybrid approach were compared with different nonlinear system identification methods. The experimental results showed that the hybrid approach performs better than the other methods in terms of root mean square error (RMSE) and correlation coefficients. The hybrid GMDH/GA approach was effective for modeling and predicting the brake pedal system under random braking conditions.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.75-80
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• 1999

Signal separation and transmission are essential for automatic breeding management of domestic animals. Electronic identification system could transmit the signal of an individual within a defined range to a personal computer by an electromagnetic signal recognition method. Signals for individual recognition were originated by controlling 12 tri-state pins of IC(PT2262) in a transmitter. PT 2262 can generate 4,096 codes. These encoded signals were modulated and transmitted with wireless lines from the transmitter. Then they were demodulated in a receiver, and the signals were transmitted to the micro-processor through an interface and were identified in a PC.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.12
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• pp.661-666
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• 2006

Interlocking signalling system plays key role as core system to manage railway operation. The core role of railway operation is to control routing, displaying signal and regulation for train. Interlocking system relate tightly to railway accident because collision and derailment is sometime taken place wrong route setting and signal displaying. Safety activity for interlocking system is inevitable to avoid the accident over its life cycle. The safety activity includes hazard identification and analysis, safety requirement allocation, safety plan, safety activity and ao on. The safety activity need a broad wide range work. In this paper, we concentrate on hazard identification for generic interlocking system and programmable electronic interlocking system and compare between two results. The hazards will be used for safety activity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.1
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• pp.55-66
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• 2002

Electronic cash system based on anonymous coins have been invented by David Chaum. However, von Solms and Naccache discovered that such anonymous coins also very well suited to support criminals in Blacoailing. In this paper, we suggest a method that a client informs a bank of the information about blackmailing attack by using Schnorr identification protocol of XTR version at the stage of identification, whenever he is blackmailed. In general, blackmailing is the most serious among the various drawbacks of electronic cash system. Especially, blackmiling to be done when the client is kidnapped brings a fatal result to electronic cash system. But if the Schnorr identification protocol of XTR version is used, we can efficiently defeat blackmailing without assumption required in the existing method to defeat blackmailing.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.118-124
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• 2004

In this paper, we present a indirect adaptive control method using a wavelet neural network (WNN) for the control of chaotic nonlinear systems without precise mathematical models. The proposed indirect adaptive control method includes the off-line identification and on-line control procedure for chaotic nonlinear systems. In the off-line identification procedure, the WNN based identification model identifies the chaotic nonlinear system by using the serial-parallel identification structure and is trained by the gradient-descent method. And, in the on-line control procedure, a WNN controller is designed by using the off-line identification model and is trained by the error back-propagation algorithm. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic nonlinear systems.

• Journal of the Optical Society of Korea
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• v.4 no.1
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• pp.19-22
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• 2000

A new image encoding and identification scheme is proposed for security verification by us-ing a CGH(computer generated hologram), random phase mask, and a correlation technique. The encrypted image, which is attached to the security product, is made by multiplying a QP- CGH(quadratic phase CGI) with a random phase function. The random phase function plays a key role when the encrypted image is decrypted. The encrypted image can be optically recovered by a 2-f imaging system and automatically verified for personal identification by a 4-f correlation system. Simulation results show the proposed method can be used for both the reconstruction of an original image and the recognition of an encrypted image.