• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.635-639
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the modeling of chaotic nonlinear systems. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the modeling performance for chaotic nonlinear systems and compare it with those of the FNN and the WFM.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.6 s.324
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• pp.9-15
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• 2004

In MIMO-OFDM systems, conventional channel estimation techniques using comb type training symbols give relatively large mean squared errors(MSEs) at the edge subcarriers. To reduce the MSEs at these subcarriers, a cyclic comb type training structure is proposed. In the proposed cyclic training structure, all types of training symbols are transmitted cyclically at each antenna. At the receiver, the channel frequency responses that are estimated using each training symbol are averaged with weights obtained from the corresponding MSEs. Computer simulations showed that the proposed cyclic training structure gives more SNR gain than the conventional training structure.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.2
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• pp.12-19
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• 2001

In this paper, we propose the new algorithm which can design on the optimal structure of modular system. This system is composed to the wavelet neural network in order to simplify the structure of modular system and use the time-frequency analysis. We will determine the number of module and node of each sub-system using the proposed algorithm. This algorithm provides the methodology, which we will design optimal structure of modular wavelet neural network through analyzing the character of system. We apply the proposed new structure and algorithm to approximation problem and evaluate the effectiveness of the proposed system and algorithm.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2856-2858
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• 1999

In this paper, the FPNN(Fuzzy Polynomial Neural Networks) algorithm with multi-layer fuzzy inference structure is proposed for the model identification of a complex nonlinear system. The FPNN structure is generated from the mutual combination of PNN (Polynomial Neural Network) structure and fuzzy inference method. The PNN extended from the GMDH(Group Method of Data Handling) uses several types of polynomials such as linear, quadratic and modifled quadratic besides the biquadratic polynomial used in the GMDH. In the fuzzy inference method, simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used Each node of the FPNN is defined as a fuzzy rule and its structure is a kind of fuzzy-neural networks. Gas furnace data used to evaluate the performance of our proposed model.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.377-377
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• 2010

FINEMET type nanocrystalline materials synthesized by controlled crystallization of amorphous ribbons[1] exhibit excellent soft magnetic properties making them attractive for technological applications. Present work reports the electronic structure studies of Co-substituted FINEMET to get information on the effect of successive Co substitution on local environment around Fe and Co atom by using near edge x-ray absorption fine structure (NEXAFS) and x-ray magnetic circular dichroism (XMCD) measurements. NEXAFS spectroscopy and XMCD measurements have been carried out at Fe $L_{3,2}$ and Co $L_{3,2}$-edges to investigate the chemical states and electronic structure of FINEMET [$(Fe_{100-x}Co_x)_{78}Si_9Nb_3Cu_1Ba$](0$L_{3,2}$-edge reveal that Fe is in 2+ state and in tetrahedral symmetry with other elements. The magnetic properties exhibiting soft magnetic behavior[2] are discussed on the basis of the electronic structure studied through XMCD.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1996.05a
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• pp.232-234
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• 1996

We have investigated the effect of molecular structure of polymer of rubbed polyimide (PI) films for surface liquid crystal alignment. To obtain surface alignment effect of Polymer molecular structure, we measured the polar (out of plane-tilt) anchoring strength and surface ordering of 5CB on rubbed PI surfaces. We have found that the polar anchoring strength of 5CB is depend on the polymer molecular structure of these unidirectionally rubbed PI surfaces.

• Journal of the Korean Magnetic Resonance Society
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• v.15 no.1
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• pp.14-24
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• 2011

We have performed Liquid Chromatography-Solid Phase Extraction-NMR (LC-SPE-NMR) analysis for liquid crystalline mixture and elucidated the structures of selected components by NMR spectra. Combining the results of one-dimensional 1H experiments as well as homonuclear and heteronuclear two-dimensional experiments, we could analyze the molecular structure of the liquid crystal singles whose structure had not been interpretable by mass spectrometry alone.

• Journal of Sensor Science and Technology
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• v.23 no.2
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• pp.105-109
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• 2014

Structure and electrical properties of $0.85NaNbO_3-0.15LiNbO_3$ ($(Li_{0.15}Na_{0.85})NbO_3$) ceramics were investigated as a function of sintering temperature. $(Li_{0.15}Na_{0.85})NbO_3$ ceramics were prepared by conventional solid state processing. A main phase of the orthorhombic perovskite structure and secondary phase of $LiNbO_3$ were confirmed for all sintered specimens. Dense $(Li_{0.15}Na_{0.85})NbO_3$ ceramics were obtained at sintering temperature above $1050^{\circ}C$. With increasing sintering temperature, the electromechanical coupling factor ($k_p$), piezoelectric constant ($d_{33}$) and relative dielectric constant (${\varepsilon}_r$) of the sintered specimens increased, while the mechanical quality factor ($Q_m$) decreased. These results are due to the increase of grain size and crystallite size of orthorhombic perovskite structure. Based on the temperature dependence of ${\varepsilon}_r$, stable piezoelectric properties were expected because no phase transition found up to $300^{\circ}C$. Typically, kp of 18%, $d_{33}$ of 34.7 pC/N, ${\varepsilon}_r$ of 135, and $Q_m$ of 62.8 were obtained for the specimens sintered at $1200^{\circ}C$ for 5 h.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.26 no.6
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• pp.421-424
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• 2013

The Hall factor in a quantum well structure with X or L-type indirect conduction valleys is calculated for various strain conditions. The two-dimensional constant energy surfaces of occupied valleys are proven to be identical. As a result, the Hall factor depends on the relative direction of occupied valleys to the growth direction, regardless of the number of occupied valleys. This work is widely applicable to the two-dimensional structure with indirect conduction minima for any growth direction and under different strain conditions.

• Journal of Magnetics
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• v.15 no.1
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• pp.1-6
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• 2010

The magnetic properties of amorphous Fe were investigated by examining the electronic structures of structurally disordered Fe systems generated from crystalline bcc and fcc Fe using a Monte-Carlo simulation. As a rst principles band method, the real space spin-polarized tight-binding linearized-mun-tin-orbital recursion method was used in the local spin density approximation. Compared to the crystalline system, the electronic structures of the disordered systems were characterized by a broadened band width, smoothened local density of states, and reduced local magnetic moment. The magnetic structures depend on the short range configurations. The antiferromagnetic structure is the most stable for a bcc-based disordered system, whereas the noncollinear spin spiral structure is more stable for a fcc-based system.