• 한국정보통신학회논문지
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• 제9권2호
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• pp.229-236
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• 2005

이 논문은 신호 f(t)의 실제적인 스케일 정보를 나타내는 웨이브렛 플랜을 중심으로 연속 웨이브렛 역변환의 특성에 대하여 논하였다. 웨이브렛 변환에 비해 역변환의 적용이 상대적으로 미비한 이유는 수치적인 연산의 복잡성에 기인한 것이며, 이 논문은 웨이브렛 역변환의 안정된 복원을 위한 방법에 대하여 연구하였다. 웨이브렛 역변환의 안정적인 구현은 신호 f(t)에 대한 실제적인 스케일 정보를 지니고 있는 웨이브렛 플랜이라는 새로운 "시간-스케일" 공간을 통하여 실현하였으며, 이는 완전한 멀티 필터 뱅크 시스템과 동일한 특성을 나타낸다. 즉 연속 웨이브렛 변환을 통해 신호 f(t)의 모든 스케일 성분을 독립적으로 주파수 전체 대역에 걸쳐 분산하고 다시 역변환을 통해 원래의 신호를 복원하는 과정은 필터뱅크이론의 분석과 합성과정과 일치한다 이 논문에서는 연속 웨이브렛 역변환을 이용하여 "시간-스케일" 필터를 통한 신호 f(t)의 스케일 분해와 웨이브렛 멀티 필터 뱅크이론에 대하여 논하였다.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.615-619
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• 2009

방향 적응적인 저대역 통과 필터를 사용한 보간 방식은 화소의 방향성에 따른 적응적인 필터 처리를 통하여 가로 세로의 비율이 다른 보간을 수행할 시 생기는 영상의 왜곡을 최소화한 방식이다. 본 방식은 하드웨어 적인 구현에 적합하도록 설계되었으며, 영상의 보간 시 사용하는 저대역 통과 필터 처리 강도의 조절이 용이하여 최종 영상의 선명도를 쉽게 변경 할 수 있다는 장점을 가지고 있다. 적은 연산량과 화질의 변경이 용이함으로 인하여, 본 기술은 디지털 카메라, CCTV, 평판 디스플레이 장치 등 영상 보간 기술이 필요한 영상 장비에 적용될 수 있다.

• 한국컴퓨터정보학회논문지
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• 제24권6호
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• pp.1-9
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• 2019

Hard disks, which have long been used as secondary storage in computing systems, are increasingly being replaced by solid state drives (SSDs), due to their relatively fast data input / output speeds and small, light weight. SSDs that use NAND flash memory as a storage medium are significantly different from hard disks in terms of physical operation and internal operation. In particular, there is a feature that data overwrite can not be performed, which causes erase operation before writing. In order to solve this problem, a hot data for frequently updating a data for a specific page is distinguished from a cold data for a relatively non-hot data. Hot data identification helps to improve overall performance by identifying and managing hot data separately. Among the various hot data identification methods known so far, there is a technique of recording consecutive write requests by using a Bloom filter and judging the values by hot data. However, the Bloom filter technique has a problem that a new bit array must be generated every time a set of items is changed. In addition, since it is judged based on a continuous write request, it is possible to make a wrong judgment. In this paper, we propose a method using a counting filter for accurate hot data verification. The proposed method examines consecutive write requests. It also records the number of times consecutive write requests occur. The proposed method enables more accurate hot data verification.

• Smart Structures and Systems
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• 제1권2호
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• 한국산학기술학회논문지
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• 제10권12호
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• pp.3638-3644
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• 2009

본 논문에서는 새롭게 제안한 선형 캐스코드 전류모드 적분기를 기본으로 구성된 다중채널 CMOS 저전압 전류모드 필터를 설계하였다. 제안된 전류모드 적분기는 기존의 전류미러형 전류모드 적분기 비해서 높은 전류이득 및 단위이득 주파수 특성을 얻을 수 있다. 5차 체비셰프 함수로써 구성한 필터는 신호흐름선도(SFG)기법에 의하여 능동필터로 변환되었다. 1.8V-$0.18{\mu}m$ CMOS 공정파라미터를 사용한 HSPICE 시뮬레이션 결과, 설계된 필터는 0.51MHz에서 7.03MHz대역까지의 주파수 조정범위를 가지며 Bluetooth, DECT, WCDMA의 3채널의 기저대역에서 사용할 수 있음을 확인하였다.

• Childhood Kidney Diseases
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• 제6권2호
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• pp.251-258
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• 2002

저자들은 다장기 부전과 패혈증에 의한 ?상태의 급성 신부전 환아 세 명에서 펌프를 이용한 CVVH를 이용하여 효과적으로 한외여과액을 유지할 수 있었던 경험을 문헌 고찰과 함께 보고하는 바이다.

• 전기학회논문지
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• 제61권1호
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• pp.117-124
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• 2012

In this paper, we present some remarks on the correlations between s and w domains when a discrete-time transfer function is converted from z-plane by using the w-transform. With time response specifications, when a digital filter or controller is designed in z-plane, the w-transform is useful for the purpose if only the w-transformed system closely approximates to the continuous-time system. It will be shown that the approximation is accomplished only in the specific region depending on sampling time. Also, it is noted that such an approximation should be carefully dealt with for the case where a discrete-time reference transfer function is synthesized for the use of direct digital design.

• 한국인공지능학회지
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• 제11권1호
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• pp.17-24
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• 2023

With the continuous growth in the amount of data collected and analyzed, deep learning has become increasingly popular for extracting meaningful insights from various fields. However, hardware limitations pose a challenge for achieving meaningful results with limited data. To address this challenge, this paper proposes an algorithm that leverages the characteristics of convolutional neural networks (CNNs) to reduce the size of image datasets by 20% through smoothing and shrinking the size of images using color elements. The proposed algorithm reduces the learning time and, as a result, the computational load on hardware. The experiments conducted in this study show that the proposed method achieves effective learning with similar or slightly higher accuracy than the original dataset while reducing computational and time costs. This color-centric dataset construction method using image smoothing techniques can lead to more efficient learning on CNNs. This method can be applied in various applications, such as image classification and recognition, and can contribute to more efficient and cost-effective deep learning. This paper presents a promising approach to reducing the computational load and time costs associated with deep learning and provides meaningful results with limited data, enabling them to apply deep learning to a broader range of applications.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.109-112
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• 2000

An algorithm for the reduction of blocking artifacts is pro-posed. Instead of filtering the pixels by a digital filter, the proposed algorithm considers the compressed image as continuous-time ,signal and replaces it by a pre-designed lowpass filter outputs. The algorithm shows better performance than the conventional methods in low activity region, and comparable or a little worse objective performance in high activity region. Hence, by applying the proposed algorithm to the low activity region and the conventional ones to the high activity region, the objective and subjective performances are improved in most cases.

• International Journal of Aeronautical and Space Sciences
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• 제13권4호
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• pp.499-506
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• 2012

In this paper, a dynamic modeling for the velocity and position information of a single frequency stand-alone GPS(Global Positioning System) receiver is described. In static condition, the position error dynamic model is identified as a first/second order transfer function, and the velocity error model is identified as a band-limited Gaussian white noise via non-parametric method of a PSD(Power Spectrum Density) estimation in continuous time domain. A Kalman filter is proposed considering both correlated/white measurements noise based on identified GPS error model. The performance of the proposed Kalman filtering method is verified via numerical simulation.