• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.59-68
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• 1999

The timing characteristics of an ASIC are analyzed based on the propagation delays of each gate and interconnect wire. The gate delay can be modeled using the two-dimensional delay table whose index variables are the input transition time and the output load capacitance. The AWE technique can be adopted as an algorithm to compute the interconnect delay. Since these delays are affected by the interaction to the two-dimensional delay table and the AWE technique. A method to model this effect has been proposed through the effective capacitance and the gate driver model under the assumption of single driving gate. This paper presents a new technique to handle the multiple CMOS gates driving interconnect wire by extending previous approach. This technique has been implemented in C language and applied to several interconnect circuits driven by multiple CMOS gates. In most cases, we found a few tens of speed-up and only a few percents of errors in computing both of gate and interconnect delays, compared to SPICE.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.6
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• pp.53-58
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• 2004

A novel UV sensor was manufactured and characterized using evanescent field coupling between photochromic dye dispersed polymer waveguide and side polished fiber. The spiroxazine (photochromic dye) dispersed polymer was used as planar waveguides. The resonant wavelength was shifted owing to refractive index variation of planar waveguide on exposed UV because of its photo-functional properties. The sensitivities are $1.21{\mu}W/mw$ and $2.75{\mu}W/mw$ when UV intensities increased after exposure times were fixed at 3 seconds and 5 seconds, respectively. Output optical power according to UV intensity increases and saturation time decreases as the intensity of UV radiations increases.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.7
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• pp.620-624
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• 2016

In this paper we designed a current mode logic frequency divider to transmit a baseband amplitude modulated signal. From simulation result, we studied input and output waveforms according to the variation of input bias voltage. For the purpose of the verification of the study, we designed a current mode logic frequency divider at 1,400 MHz. The designed frequency divider operates between 100 MHz and 3,000 MHz, for -33 dBm input power. The circuit draws $I_{total}=30mA$ from $V_{DD}=3V$ supply, and the simulation result shows that an amplitude modulated signal at 1,400 MHz with the modulation index of 0.5 was successfully downconverted to 700 MHz.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1220-1228
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• 2010

In this paper, we suggest a scheme to develop an efficient discrete nonlinear model based on polynomial structure for a RF power amplifier(PA). We describe a procedure to extract a discrete nonlinear model such as Taylor series or memory polynomial by sampling the input and output signal of RF PA. The performance of the model is analyzed varying the model parameters such as sample rate, nonlinear order, and memory depth. The results show that the relative error of the model is converged if the parameters are larger than specific values. We suggest an efficient modeling scheme considering complexity of the discrete model depending on the values of the model parameters. Modeling efficiency index(MEI) is defined, and it is used to extract optimum values for the model parameters. The suggested scheme is applied to discrete modeling of various RF PAs with various input signals such as WCDMA, WiBro, etc. The suggested scheme can be applied to the efficient design of digital predistorter for the wideband transmitter.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.61.1-61.1
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• 2017

As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT $195{\AA}$, and $304{\AA}$ from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We consider other input images which consist of last two images and their difference image. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the over-fitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). All statistical parameters do not strongly depend on the number of input data sets. Our model can immediately be applied to automatic forecasting service when image data are available.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Journal of IKEEE
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• v.24 no.2
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• pp.409-418
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• 2020

In this paper, an integrated optical, evanescent-wave biosensor utilizing a multimode interferometer based on a Si₃N₄ rib-optical waveguide consisting of the Si/SiO₂/Si₃N₄/SiO₂ stacked structure was described. The theoretical background of the multimode interferometer was reviewed, and the structure and design process were presented through numerical computational analysis. We analyzed how the dimension (length, width) of the multimode interferometer affected the sensor performance. It has been confirmed through computational analysis that the changes in the refractive index of an analyte greatly affect the mode pattern formation position and output optical power of a multimode interferometer, and proved that this principle could be applied to integrated-optic biosensor.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.105-110
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• 2015

This paper relates with the eualization performance of Constellation Matching-MMA (CM-MMA) in order to the consists of optimum receiver for the minimization of intersymbol interference and additive noise effects that is occurs in the nonlinear communication channel. The error signal were obtained that combines the Constellation Matching technique that inserts the zero point between the signal point of equalizer for improving the residual isi and convergence speed compared to the currently used MMA algorithm. In the initial state of adaptive equalization, it depends on the MMA characteristics mainly. And in the steady state, it depends on the CM characteristics mainly. In order to analyzing the equalization performance, the output signal constellation, residual isi, maximum distortion, MSE and SER were applied, then it were compared with the present MMA algorithm. As a result of computer simulation, the CM-MMA has more better performance in the every performance index, and it was also confirmed that the constellation matching effect can be obtained in the greater than 20dB signal to noise ratio.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.105-110
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• 2018

This paper compare the adaptive equalization performance of NM-MMA (Novel Mixed-MMA) algorithm which using the mixed const function by scaling factor values. The mixed cost function of NM-MMA composed of the appropriate weighted addition of gradient vector in the MMA and SE-MMA cost function, and updating the tap coefficient based on these function, it is possible to improve the convergence speed and MSE value of current algorithm. The computer simulation was performed in the same channel, step size, SNR environment by changing the scaling factor, and its performance were compared appling the equalizer output constellation, residual isi, MD, MSE, SER. As a result of computer simulation, the residual values of performance index were reduced in case of the scaling factor of MMA cost function was greater than the scaling factor of SE-MMA. and the convergence speed was improved in case of the scaling factor of SE-MMA was greater than the MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.91-97
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• 2016

This paper evaluates the equalization algorithm of FC-MMA (Fast Convergence-Multi Modulus Algorithm) and RMMA (Region based Multi Modulus Algorithm) for the compensation of intersymbol interference which is due to the distortion of communication channel. In order to obtain the error signal for adaptive equalization, the FC-MMA use the modified dispersion constant considering the number of signal symbol, the RMMA separates the 4 region which every symbol points are located, then reduce the symbol point based on this region into constant modulus symbol point. By applying the different principle in order to get the error signal for the updating the tap coefficient of adaptive equalizer, it has the different equalization performance by these error signal. The computer simulation was performed in order to compare the different equalization performance in this paper. The performance index includes the output signal constellation, the residual isi and maximum distortion that is for the convergence characteristics, the SER. As a result of computer simulation, RMMA has more good performance in the residual isi, maximum distortion after in steady state and SER performance than FC-MMA, but not in convergence speed to reach the steady state.