• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.65-72
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• 2006

In digital signal processing, the polyphase decomposition of signal has been often used in the implementation of multirate system. Especially, in the design of digital filter and so forth the method in very useful to improve the performance of various algorithms because it provides the multi-channel for paralled processing. Generally, the polyphase-decomposed signals tend to expand the frequency band by including more high frequencies than original signal from decimation for down sampling. This property brings about the significant limitation in the structure or the performance of digital polyphase signal processing system. In this paper we theoretically propose a perfect band compression and reconstruction method for polyphase component signals, then experimentally show its effectiveness through Matlab simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.513-517
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• 2005

The condition monitoring of rotating machinery such as turbines, pumps and compressors, determine what repairs are needed to avoid shutdown and disassembly of the machine in an industrial plant Many diagnosis methods have been developed for use when the machine is running at steady state, the stationary condition. But much information can be gained about a rotor's condition during non-stationary conditions such as run-up and run-down. Order tracking analysis is a powerful tool for analyzing the condition of a rotating machine when its speed changes over time. Powerful OTA using digital signal processing has some advantages(cheap hardware, the powerful methods, the accurate post processing) and also some disadvantages(calculation time, high speed sampling). New OTA tool based on the chirplet transform is similar to the short time Fourier transform. But, it has good resolution at high speed like other OTA methods based STFT and more resolution for constant frequency components than re-sampling OTA.

• Journal of Institute of Convergence Technology
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• v.7 no.2
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• pp.25-30
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• 2017

This paper presents the effects of a virtual mass with a low-pass filter on the stability boundary of a virtual spring in the haptic system. In general, a haptic system consists of a haptic device, a sampler, a virtual impedance model and zero-order-hold. The virtual impedance is modeled as a virtual spring and a virtual mass. However the high-frequency noise due to the sampling time and the quantization error of sampled data may be generated when an acceleration is measured to compute the inertia force of the virtual mass. So a low-pass filter is needed to prevent the unstable behavior due to the high-frequency noise. A finite impulse response (FIR) filter is added to the measurement process of the acceleration and the effects on the haptic stability are simulated. According to the virtual mass with the FIR filter and the sampling time, the stability boundary of the virtual spring is analyzed through the simulation. The maximum available stiffness to guarantee the stable behavior is reduced, but simulation results still show that the stability boundary of the haptic system with the virtual mass is larger than that of the haptic system without the virtual mass.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.141-148
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• 2012

A design of a 32-bit fourth-stage decimation filter decimation filter used in sigma-delta analog-to-digital (A/D) converter is proposed in this work. A four-stage decimation filter with down-sampling factor of 512 and 32-bit output is developed. A multi-stage cascaded integrator-comb (CIC) filter, which reduces the sampling rate by 64, is used in the first stage. Three half-band FIR filters are used after the CIC filter, each of which reduces the sampling rate by two. The pipeline structure is applied in the CIC filter to reduce the power consumption of the CIC. The Canonic Signed Digit (CSD) arithmetic is used to optimize the multiplier structure of the FIR filter. This filter is implemented based on a semi-custom design flow and a 130nm CMOS standard cell library. This decimation filter operates at 98.304 MHz and provides 32-bit output data at an audio frequency of 192 kHz with power consumption of $697{\mu}W$. In comparison to the previous work, this design shows a higher performance in resolution, operation frequency and decimation factor with lower power consumption and small logic utilization.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.2
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• pp.126-136
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• 1997

When we apply the spectrally efficient quadrature amplitude modulation(QAM) to mobile communications, it is necessary to estimate and compensate the channel charac- teristics. In this paper, a new type fading estimation method for PSAM using sinc function is presented. Gaussian interpolation method has a drawback that the performance degrades rapidly if pilot symbol period increases even though pilot sysbol period is less than Nyquist sampling rate. The Wiener filter method does not degrade until pilot symbol period is equal to the Nyquist sampling rate. It is difficult for Wiener filter method to be applied to real system because autocorrelation function of channel gain, Doppler frequency and SNR(signal to noise ratio) must be known to optimize the filter coefficients. But proposed method has a similar performance to the Wiener filter method, and does not need to know the autocorrelation function of channel gain, the doppler frequency and SNR. Therefore the proposed method cna be applied to real system easily.

• Korean Journal of Optics and Photonics
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• v.34 no.5
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• pp.192-201
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• 2023

The band-limited angular spectrum method (BL-ASM) causes aliasing errors due to spatial frequency control problems. In this paper, a sampling interval adjustment technique for phase holograms and a technique for reducing speckle noise and improving image quality using a deep-learningbased U-net model are proposed. With the proposed technique, speckle noise is reduced by first calculating the sampling factor and controlling the spatial frequency by adjusting the sampling interval so that aliasing errors can be removed in a wide range of propagation. The next step is to improve the quality of the reconstructed image by learning the phase hologram to which the deep learning model is applied. In the S/W simulation of various sample images, it was confirmed that the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were improved by 5% and 0.14% on average, compared with the existing BL-ASM.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.411-424
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• 2017

An all-digital delay-locked loop (DLL) for a mobile memory interface, which runs at 0.11-2.5 GHz with a phase-shift capability of $180^{\circ}$, has two internal DLLs: a global DLL which uses a time-to-digital converter to assist fast locking, and shuts down after locking to save power; and a local DLL which uses a phase detector with an adaptive phase sampling window (WPD) to reduce jitter accumulation. The WPD in the local DLL adjusts the width of its sampling window adaptively to control the loop bandwidth, thus reducing jitter induced by UP/DN dithering, input clock jitter, and supply/ground noise. Implemented in a 65 nm CMOS process, the DLL operates over 0.11-2.5 GHz. It locks within 6 clock cycles at 0.11 GHz, and within 17 clock cycles at 2.5 GHz. At 2.5 GHz, the integrated jitter is $954fs_{rms}$, and the long-term jitter is $2.33ps_{rms}/23.10ps_{pp}$. The ratio of the RMS jitter at the output to that at the input is about 1.17 at 2.5 GHz, when the sampling window of the WPD is being adjusted adaptively. The DLL consumes 1.77 mW/GHz and occupies $0.075mm^2$.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.87-96
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• 2019

Low power issue is one of the most critical problems in the Internet of Things (IoT), which are powered by battery. To solve this problem, various approaches have been presented so far. In this paper, we propose a method to reduce the power consumption by reducing the numbers of accesses into the flash memory consuming a large amount of power for on-chip software execution. Our approach is based on using cooperative logging structure to distribute the sampling overhead in single sensor node to adjacent nodes in case of rare-event applications. The proposed algorithm to identify event occurrence is newly introduced with negative feedback method by observing difference between past data and recent data coming from the sensor. When an event with need of flash access is determined, the proposed approach only allows access to write the sampled data in flash memory. The proposed event detection algorithm (EDA) result in 30% reduction of power consumption compared to the conventional flash write scheme for all cases of event. The sampled data from the sensor is first traced into the random access memory (RAM), and write access to the flash memory is delayed until the page buffer of the on-chip flash memory controller in the micro controller unit (MCU) is full of the numbers of the traced data, thereby reducing the frequency of accessing flash memory. This technique additionally reduces power consumption by 40% compared to flash-write all data. By sharing the sampling information via LoRa channel, the overhead in sampling data is distributed, to reduce the sampling load on each node, so that the 66% reduction of total power consumption is achieved in several IoT edge nodes by removing the sampling operation of duplicated data.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.105-115
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• 2018

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results of frequency based snowfall depth show that most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. According to the results, observed data and Bootstrap method showed a difference of -19.2% to 3.9%, and the Bootstrap method and SIR(Sampling Importance Resampling) algorithm showed a difference of -7.7 to 137.8%. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.11
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• pp.1074-1080
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• 2013

The low phase noise and wideband frequency synthesizer has been designed by using YTO. Offset PLL structure is used for reducing a division ratio of feedback loop. The phase noise modeling is applied to optimize loop filter of PLL and YTO module. And DDS is used as reference signal of frequency synthesizer for fine resolution. The fabricated wideband frequency synthesizer has the output frequency of 3.2 GHz to 6.8 GHz, phase noise of -107 dBc/Hz at 10 kHz offset from the carrier and frequency resolution of 1 Hz. The measured phase noise is well agreed with the simulated one.