• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.499-505
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• 2011

In this paper, we proposed an adaptive fuzzy sliding mode control for nonlinear systems without parameter projection method. By modifying the controller structure, the parameters of the estimated input gain function are guaranteed not being identically zero and it is shown that the control scheme will not cause any implementation problem even if the estimated value of input gain function is zero at any moment during on-line operations. Except for the input gain function which an approximate estimate for its lower bound is needed, the proposed control scheme does not assume a priori the exact values of the bounding parameters. Based on Lyapunov synthesis methods, the overall control system guarantees that the tracking error asymptotically converges to zero and that all signals involved in controller are uniformly bounded. This can be illustrated by the simulation results for an inverted pendulum system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.181-192
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• 2003

Blind equalization of communication channel is important because it does not need training signal, nor does it require a priori channel information. So, we can increase the bandwidth efficiency. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind channel equalizer length mismatch as well as for its simple adaptive implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary decision delay. In this paper, we propose method for fractionally spaced blind equalizer with arbitrary decision delay using one-step forward prediction error filter from second-order statistics of the received signals for SIMO channel. Our algorithm utilizes the forward prediction error as training signal and computes the best decision delay from all possible decision delay. Simulation results are presented to demonstrate the performance of our proposed algorithm.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.5
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• pp.1154-1161
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• 2005

Yin Yang theory is the first and the last one to interpret diseases apply to treatment in oriental medicine. So it is regarded as the way of heaven and earth, the discipline of all things, the origin of change, the beginning of giving birth and death, the source of spirit. These regulatory passages are needed to compare with western medical physiology and analyzed whether it has scientific bases or not. The Yin Yang theory of traditional oriental medicine are summerized from the descriptions of Scripture of Documents, Ying Wei theory of Huangdi Neijing. Meanwhile up-to-date neurobiological and molecular genetic theories on circadian physiology are reviewed in western medicine. Sunshine is transferred through RGC to SCN, herein the central circadian rhythm is made by zeitgeber and interaction of melatonin secreted from pineal body and orexin from mp pan of hypothalamus. So HPA axis is activated and controlled under the circadian rhythm and affects peripheral tissues and cells of whole body through glucocorticoid hormones. First of all, the circadian rhythm makes the basic patterns of human life in biological and sociological meaning. It is almost same context with the record of the Scripture of Documents. Also the Ying Qi and Wei Qi is basically same with the sleep-awake mechanism, that is melatonin/orexin signal or per/clk/bmal/cry genes with circadian activation and activity of each organ's physiological function. Conclusively it can be said that Yin Yang is a priori principle of living things and the beginning of giving birth and death for activation of them biologically, as is described in Huangdi Neijing.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.737-743
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• 2014

For single image super resolution (SR), interpolation based and example based algorithms are extensively used. The interpolation algorithms have the strength of theoretical simplicity. However, those algorithms are tending to produce high resolution images with jagged edges, because they are not able to use more priori information. Example based algorithms have been studied in the past few years. For example based SR, the nearest neighbor based algorithms are extensively considered. Among them, neighbor embedding (NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the sizes of local training sets are always too small. So, NE algorithm is weak in the performance of the visuality and quantitative measure by the poor generalization of nearest neighbor estimation. An improved NE algorithm with Support Vector Regression (SVR) was proposed to solve this problem. Given a low resolution image, the pixel values in its high resolution version are estimated by the improved NE. Comparing with bicubic and NE, the improvements of 1.25 dB and 2.33 dB are achieved in PSNR. Experimental results show that proposed method is quantitatively and visually more effective than prior works using bicubic interpolation and NE.

• Membrane Journal
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• v.13 no.1
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• pp.37-46
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• 2003

The electrokinetic effect can be found in cases of the fluid flowing across the charged membrane micropores. The externally applied body force originated from the electrostatic interaction between the nonlinear Poisson-Boltzmann field and the flow-induced electrical field is taken into the equation of motion. The electrostatic potential profile is computed a priori by applying the finite difference scheme, and an analytical solution to the Navier-Stokes equation of motion for slit-like pore is obtained via the Green's function. An explicit analytical expression for the flow-induced streaming potential is derived as functions of relevant physicochemical parameters. The influences of the electric double layer, the surface potential of the wall, and the charge condition of the pore wall upon the velocity profile as well as the streaming potential are examined. With increasing of either the electric double layer thickness or the surface potential, the average fluid velocity is entirely reduced, while the streaming potential increases.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.4
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• pp.22-30
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• 2008

In this paper, we deal with modulation classification method using WT capable of classifying incident digital signals without a priori information. These key features should have good properties of sensitive with modulation types and insensitive with SNR variation. The 4 key features for modulation recognition are selected using WT coefficients, which have the property of insentive to the changing of noise. The numerical simulations for classifying 8 digital modulation types using these features are peformed. The numerical simulations of the 3 types (i.e. DTC, MDC, and SVMC) of modulation classifiers are performed the investigation of classification accuracy and execution time to design the modulation classification module in software radio. The simulation result indicated that the execution time of MDC and DTC was best and MDC and SVMC showed good classification performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.1
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• pp.55-63
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• 2013

Digital retrodirective antenna system is easy to modify and upgrade because it can control the phase information of the output signal toward opposite direction to input signal without a priori knowledge of the arrival direction. Due to this advantage, it is possible to do fast beam tracking. Especially, we need to design the digital PLL performance for the digital retrodirective array antenna system. So, in this paper the settling time of phase estimator and BER performance of retrodirective antenna system are investigated according to design of filter in digital PLL. When QAM signal is used for 1 Mbps with $30^{\circ}$ of phase delay, simulation results show that digital phase conjugation technique has better BER performance by about 1 dB than non-phase conjugation system when digital filter is stable. If not, the system can't estimate the exact phase because of oscillation of filter.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.97-103
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• 2018

In this paper, the estimation method for the power signal harmonics is proposed by using the time-varying optimal finite impulse response (FIR) filter. To estimate the magnitude and phase-angle of the harmonic components, the time-varying optimal FIR filter is designed for the state space representation of the noisy power signal which the magnitude and phase is considered as a stochastic process. Since the time-varying optimal FIR filter used in the proposed method does not use any priori information of the initial condition and has FIR structure, the proposed method could overcome the demerits of Kalman filter based method such as poor estimation and divergence problem. Due to the FIR structure, the proposed method is more robust against to the model uncertainty than the Kalman filter. Moreover, the proposed method gives more general solution than the time-invariant optimal FIR filter based harmonic estimation method. To verify the performance and robustness of the proposed method, the proposed method is compared with time-varying Kalman filter based method through simulation.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1131-1131
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• 2001

To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

• Journal of the Korean association of regional geographers
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• v.16 no.4
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• pp.355-368
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• 2010

This study is to make a framework of newly interpretating the dynamic change of regional or local landscape rapidly occurred after the establishment of the nation state and capitalistic system. The basic concepts of making an interpretative framework are power, subjectivity, and performativity. The framework of closely interrelating the three concepts developed in the near future will be applied to the interpretation of variety of (de)centralized landscapes in regions or locals. A centralized political power under the nation state has destroyed or marginalized the historically developed landscapes, traditional culture, and subjects' values in regions or locals by the political implementation of the nation state, the establishment of national identity, a centralized economic development, and so on. The landscapes produced by the political power of the nation state can take a role as a cause of conflicts in regions or locals in terms of a historical perspective. Landscapes are being made by various subjects, and the produced landscapes also positively or negatively will influence the emotion, cognition, and behavior of the subjects particularly in a performative perspective. The dynamics interrelation between subjects and landscapes has been disguised or marginalized by reason/rationality, totality/collectivity, the separation between reason and emotion mainly made by modernism, the nation state, a capitalistic system. The interrelation between landscapes and subjects is especially emphasized on people's resistibility and creativity. Lastly, landscape is not a concept given as a priori or (re)presented objectively. It is not also a material or an object independently existed from a subject's emotion and cognition. It should be interpreted through a performative relation with subjects. Performativity will take an active role of combining the materiality of landscape, power, and subjectivity. It is also important to understand the active role of landscapes.