• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.3
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• pp.2-17
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• 1999

Interpolated second order polynomials(ISOP's) are proposed to design efficient cascaded integrator-comb(CIC)-based decimation filters for a programmable downconverter. It is shown that some simple ISOP's can effectively reduce the passband droop caused by CIC filtering with little degradation in aliasing attenuation. In addition, ISOP's are shown to be useful for simplifying halfband filters that usually follow CIC filtering. As a result, a modified half band filter(MHBF) is introduced which is simpler than conventional halfband filters. The proposed decimation filter for a programmable downconverter is a cascade of a CIC filter, an ISOP, MHBF's and a programmable finite impulse response(FIR) filter. A procedure for designing the decimation filter is developed. In particular, an optimization technique that simultaneously designs the decimation filter is developed. In particular, an optimization technique that simultaneously designs the ISOP and programmable FIR filters is presented. Design examples demonstrate that the proposed method leads to more efficient programmable downconverters than existing ones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.918-923
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• 2009

In this paper, a design method of the compact narrow band filter on the microstrip board is proposed using complementary split-ring resonators(CSRRs). The design technique of this filter is based on cascading filter stages consisting of the combination of circular CSRRs, capacitive gaps between patches, and inductive grounded stubs with the meander configuration. By these means, it was possible to get the nearly symmetric frequency responses, adjustable bandwidths, compact sizes. And also excellent characteristic of the out-of-band rejection is achieved in contrast to the conventional filter design technique. The measured insertion shows good results about -4.0dB at the center frequency($f_0=1GHz$) and passband return loss is less than -9.4dB. The 3dB fractional bandwidth(FBW) is approximately 4%. The results of the frequency response measured on the fabricated band pass filter substrate show satisfactory agreement with the simulated frequency responses by the HFSS in the region of interest.

• Smart Structures and Systems
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• v.22 no.4
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• pp.399-411
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• 2018

The difficulty in modeling complex nonlinear structures lies in the presence of significant sources of uncertainties mainly attributed to sudden changes in the structure's behavior caused by regular aging factors or extreme events. Quantifying these uncertainties and accurately representing them within the complex mathematical framework of Structural Health Monitoring (SHM) are significantly essential for system identification and damage detection purposes. This study highlights the importance of uncertainty quantification in SHM frameworks, and presents a comparative analysis between intrusive and non-intrusive techniques in quantifying uncertainties for SHM purposes through two different variations of the Kalman Filter (KF) method, the Ensemble Kalman filter (EnKF) and the Polynomial Chaos Kalman Filter (PCKF). The comparative analysis is based on a numerical example that consists of a four degrees-of-freedom (DOF) system, comprising Bouc-Wen hysteretic behavior and subjected to El-Centro earthquake excitation. The comparison is based on the ability of each technique to quantify the different sources of uncertainty for SHM purposes and to accurately approximate the system state and parameters when compared to the true state with the least computational burden. While the results show that both filters are able to locate the damage in space and time and to accurately estimate the system responses and unknown parameters, the computational cost of PCKF is shown to be less than that of EnKF for a similar level of numerical accuracy.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.387-393
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• 2002

The enhancement technique of noise signal using mixture HFM (Midden Filter Model) are proposed. Given the parameters of the clean signal and noise, noisy signal is modeled by a linear state-space model with Markov switching parameters. Estimation of state vector is required for estimating original signal. The estimation procedure is based on mixture interacting multiple model (MIMM) and the estimator of speech is given by the weighted sum of parallel Kalman filters operating interactively. Simulation results showed that the proposed method offers performance gains relative to the previous results with slightly increased complexity.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.396-401
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• 2003

Electrical impedance tomography(EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents and measured voltages on the surface of the object. In this paper, an effective dynamic EIT imaging scheme is presented based on the projection filtering to estimate the unknown resistivity distribution. In particular, pre-integration (pre-grouping) technique is employed to stabilize the inverse algorithm. We carried out computer simulations with synthetic data to illustrate the reconstruction performance of the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.108-116
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• 2018

In this paper, we propose an image enhancement method based on Multi-Scale Retinex theory that designs Unsharp Masking Filter (UMF) and emphasizes the contrast ratio adaptively. Unsharp Masking (UM) technique emphasizes image sharpness and improves contrast ratio by adding high frequency component to the original image. The high frequency component is obtained by differentiating between original image and low frequency image. In this paper, we present how to design an UMF kernel and to adaptively apply it to increase the contrast ratio according to multi-scale retinex theory which resembles human visual system. Experimental results show that the proposed method has better quantitative performance indexes such as PSNR, ambe & SSIM and better qualitative feature like halo artifact suppression.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.8
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• pp.1482-1488
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• 2010

Recently to increase the productivity and improve the quality in the industrial process, suppressing the residual vibration in motion control systems becomes the essential problem to solve. One of the methods to suppress the residual vibration is the input shaping technique. It is based on parameters of the system model; however, the parameters are usually difficult to obtain. This paper shows the effects of the residual vibration caused by the variation of the general velocity profile for the system with two vibration modes, and also shows the effects of the input shaping filter based on the parameters of system model. Finally, the simulation results show that the proposed input shaping filter using an artificial immune algorithm is more effective for suppressing residual vibrations than genetic algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.777-782
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• 2011

Neural network technique is widely employed in the fields of signal processing, control systems, pattern recognition, etc. Learning of neural networks is an important procedure to accomplish dynamic system modeling. This paper presents a novel learning approach for differential neural network models based on the Kalman-Bucy filter theory. We construct an augmented state vector including original neural state and parameter vectors and derive a state estimation rule avoiding gradient function terms which involve to the conventional neural learning methods such as a back-propagation approach. We carry out numerical simulation to evaluate the proposed learning approach in nonlinear system modeling. By comparing to the well-known back-propagation approach and Kalman-Bucy filtering, its superiority is additionally proved under stochastic system environments.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.199-203
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• 2013

In this paper, a fast algorithm of discrete cosine transform-based interpolation filter (DCT-IF) for HEVC (high efficiency video coding) encoder is proposed. DCT-IF filter accounts for around 30% of encoder complexity, according to the computational complexity analysis with the HEVC reference software. In this work, the proposed DCT-IF is optimized by applying frame-level interpolation, SIMD optimization, and task-level parallelization via OpenMP on a developed C-based HEVC encoder. Performance analysis is conducted by measuring speed-up factor of the proposed optimization technique on the developed encoder. The results show that speed-up factors by frame-level interpolation, SIMD, and OpenMP are approximately 38-46, 3.6-4.4, and 3.0-3.7, respectively. In the end, we achieved the speed-up factor of 498.4 with the proposed fast algorithm.