• Korean Journal of Optics and Photonics
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• v.8 no.6
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• pp.492-499
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• 1997

We proposed and studied an all-optical switching device made of a bent nonlinear waveguide and an all-optical logic gate made of a bent nonlinear Y-junction. The proposed devices as switch and a logic function are based on the evolution of nonlinear guided wave along a bent nonlinear waveguide. Since the characteristics of beam propagation depens on the nonlinearity, input power and bent angle of waveguide, the characteristics of output power transmission is calculated by variation the such parameters. Furthermore, by calculating the output power through the nonlinear media with different positions of detector in nonlinear media, we could find the ideal digital switching performance at specific position of detector and implement several all-optical logic functions (AND, OR, XOR) by power contrast between waveguide end and nonlinear media.

• Geomechanics and Engineering
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• v.12 no.2
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• pp.239-255
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• 2017

Various centrifuge model tests on the pile foundations were performed to investigate fundamental characteristics of a pile-soil-foundation system recently, but it is hard to find numerical analysis results of a pile foundation system considering the nonlinear behavior of soil layers due to the dynamic excitations. Numerical analyses for a pile-soil system were carried out to verify the experimental results of centrifuge model tests. Centrifuge model tests were performed at the laboratory applying 1.5 Hz sinusoidal base input motions, and nonlinear numerical analyses were performed utilizing a finite element program of P3DASS in the frequency domain and applying the same input motions with the intensities of 0.05 g~0.38 g. Nonlinear soil properties of soil elements were defined by Ramberg-Osgood soil model for the nonlinear dynamic analyses. Nonlinear numerical analyses with the P3DASS program were helpful to predict the trend of experimental responses of a centrifuge model efficiently, even though there were some difficulties in processing analytical results and to find out unintended deficits in measured experimental data. Also nonlinear soil properties of elements in the system can be estimated adequately using an analytical program to compare them with experimental results.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1331-1333
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• 2001

In this study a measurement equipment was designed and made for the nonlinear dielectric constants in dielectrics. The determining method of the nonlinear dielectric constants also was proposed. The measurement equipment was consisted of the wave generation part, the high voltage amplifier part, the measurement part and the data acquisition part. In this equipment the measurement control and the data processing could be conducted by computer. In order to determine the nonlinear dielectric constants alternating sign-wave electric fields are applied to dielectrics with different magnitude and the waves of the electric fields and the response from dielectrics are stored in computer memories. The harmonics of dielectric displacement are obtained by the Fourier transformation of these waves. The nonlinear dielectric constants are determined at the relatively low-field region. The experiment for PZT ceramic samples was done by the equipment and the determining method and as the result meaningful data were obtained.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.271-279
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• 2007

We suggest a novel method for the evaluation of cochlear implant (CI) speech processing strategy based on neural spike train decoding. From formant trajectories of input speech and auditory nerve responses responding to the electrical pulse trains generated from a specific CI speech processing strategy, optimal linear decoding filter was obtained, and used to estimate formant trajectory of incoming speech. Performance of a specific strategy is evaluated by comparing true and estimated formant trajectories. We compared a newly-developed strategy rooted from a closer mimicking of auditory periphery using nonlinear time-varying filter, with a conventional linear-filter-based strategy. It was shown that the formant trajectories could be estimated more exactly in the case of the nonlinear time-varying strategy. The superiority was more prominent when background noise level is high, and the spectral characteristic of the background noise was close to that of speech signals. This confirms the superiority observed from other evaluation methods, such as acoustic simulation and spectral analysis.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.86-92
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• 2001

Various array processing techniques to identify the noise source position or bearing have been developed. Typical array processing techniques which are based on time delay between received signals at two sensors, are classified as conventional beamforming, correlation function and NAH (Near-Field Acoustic Holography) techniques which have their own characteristics with respect to application field and signal processing method. In this study, correlation function technique which could be applied for broadband noise source detection, is adopted and the effective detection technique is proposed considering the effects of source bandwidth and measurement noise correlation of noise sources. The validity of the Proposed technique is evaluated using the 3-dimensional nonlinear any which does not give 3-dimensional Position or bearing ambiguity

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.591-596
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• 2011

Image denoising is a key issue in all image processing researches. Generally, the quality of an image could be corrupted by a lot of noise due to the undesired conditions of image acquisition phase or during the transmission. Many approaches to image restoration are aimed at removing either Gaussian or impulse noise. Nevertheless, it is possible to find them operating on the same image, which is called mixed noise and it produces a hard damage. In this paper, we proposed noise type classification method and a mixed nonlinear filter for mixed noise suppression. The proposed filtering scheme applies a modified adaptive switching median filter to impulse noise suppression and an efficient nonlinear filer was carried out to remove Gaussian noise. The simulation results based on Matlab show that the proposed method can remove mixed Gaussian and impulse noise efficiently and it can preserve the integrity of edge and keep the detailed information.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.238-242
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• 2013

We consider the problem of constructing observers for nonlinear systems with unknown inputs. Connectionist networks, also called neural networks, have been broadly applied to solve many different problems since McCulloch and Pitts had shown mathematically their information processing ability in 1943. In this thesis, we present a genetic neuro-control scheme for nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• Computers and Concrete
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• v.18 no.5
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• pp.1019-1039
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• 2016

In this paper, a parallel algorithm of nonlinear dynamic analysis of three-dimensional (3D) reinforced concrete (RC) frame structures based on the platform of graphics processing unit (GPU) is proposed. Time integration is performed using Newmark method for nonlinear implicit dynamic analysis and parallelization strategies are presented. Correspondingly, a parallel Preconditioned Conjugate Gradients (PCG) solver on GPU is introduced for repeating solution of the equilibrium equations for each time step. The RC frames were simulated using fiber beam model to capture nonlinear behaviors of concrete and reinforcing bars. The parallel finite element program is developed utilizing Compute Unified Device Architecture (CUDA). The accuracy of the GPU-based parallel program including single precision and double precision was verified in comparison with ABAQUS. The numerical results demonstrated that the proposed algorithm can take full advantage of the parallel architecture of the GPU, and achieve the goal of speeding up the computation compared with CPU.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.842-847
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• 2005

This paper proposes a novel real-time EMG pattern recognition for the control of a multifunction myoelectric hand from four channel EMG signals. To cope with the nonstationary signal property of the EMG, features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a linear-nonlinear feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. We implement a real-time control system for a multifunction virtual hand. From experimental results, we show that all processes, including virtual hand control, are completed within 125 msec, and the proposed method is applicable to real-time myoelectric hand control without an operation time delay.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.874-879
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• 1992

It is shown that there exists a nonlinear mappping which transforms features and their changes to the desired camera motion without measurement of the relative distance between the camera and the part, and the nonlinear mapping can eliminate several difficulties encountered when using the inverse of the feature Jacobian as in the usual feature-based visual feedback controls. And instead of analytically deriving the closed form of such a nonlinear mapping, a fuzzy membership function (FMF) based neural network is then proposed to approximate the nonlinear mapping, where the structure of proposed networks is similar to that of radial basis function neural network which is known to be very useful in function approximations. The proposed FMF network is trained to be capable of tracking moving parts in the whole work space along the line of sight. For the effective implementation of proposed IMF networks, an image feature selection processing is investigated, and required fuzzy membership functions are designed. Finally, several numerical examples are illustrated to show the validities of our proposed visual servoing method.