• Title/Summary/Keyword: time domain data

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Comparison of Time-Domain Imaging Algorithms for Ultra-Wideband Radar with One-Dimensional Synthetic Aperture (1차원 합성 개구면을 가진 초광대역 레이더의 시영역 기반 영상화 기법 비교)

  • Kim, Dae-Man;Hong, Jin-Young;Kim, Kang-Wook
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.19 no.10
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    • pp.1175-1184
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    • 2008
  • Delay-sum back projection(DSBP) algorithm and the time reversal algorithm based on the finite-difference time-domain method are compared. The two algorithms, which operate in the time domain, can process the ultra-wideband (UWB) radar data to generate images that are close to the original location and shape of the target. For the experiment, the UWB radar consists of a network analyzer, a resistive V dipole antenna, a scanner, and a control computer. The radar aperture is synthesized by linearly scanning the antenna. A calibration procedure is applied to the measured data to remove signal distortion and clutter. The two algorithms are applied to the same data on the same platform. It is shown that the DSBP algorithm produces better images but takes longer time to produce the images than the FDTD-TR algorithm.

Bootstrap methods for long-memory processes: a review

  • Kim, Young Min;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • v.24 no.1
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    • pp.1-13
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    • 2017
  • This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

Efficient time domain equalizer design for DWMT data transmission (DWMT 데이타 전송을 위한 효율적인 시간영역 등화기 설계)

  • 홍훈희;박태윤;유승선;곽훈성;최재호
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.69-72
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    • 1999
  • In this paper, an efficient time domain equalization algorithm for discrete wavelet multitone(DWMT) data transmission is developed. In this algorithm, the time domain equalizer(TEQ) consists of two stages, i.e., the channel impulse response shortening equalizer(TEQ-S) in the first stage and the channel frequency flattening equalizer(TEQ-F) in the second stage. TEQ-S reduces the length of transmission channel impulse response to decrease intersymbol interference(ISI) followed by TEQ-F that enhances the channel frequency response characteristics to the level of an ideal channel, hence diminishes the bit error rate. TEQ-S is implemented using the least-squares(LS) method, while TEQ-F is designed by using the least mean-square(LMS) algorithm. Since DWMT system also requires of the frequency domain equalizer in order to further reduce ICI and ISI the hardware complexity is an another concern. However, by adopting an well designed and trained TEQ, the hardware complexity of the whole DWMT system can be greatly reduced.

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Damage Detection in Time Domain on Structural Damage Size (구조물의 손상크기에 따른 시간영역에서의 손상검출)

  • Kwon Tae-Kyu;Yoo Gye-Hyoung;Lee Seong-Cheol
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.6 s.183
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    • pp.119-127
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    • 2006
  • A non-destructive time domain approach to examine structural damage using parameterized partial differential equations and Galerkin approximation techniques is presented. The time domain analysis for damage detection is independent of modal parameters and analytical models unlike frequency domain methods which generally rely on analytical models. The time history of the vibration response of the structure was used to identify the presence of damage. Damage in a structure causes changes in the physical coefficients of mass density, elastic modulus and damping coefficients. This is a part of our ongoing effort on the general problem of modeling and parameter estimation for internal damping mechanisms in a composite beam. Namely, in detecting damage through time-domain or frequency-domain data from smart sensors, the common damages are changed in modal properties such as natural frequencies, mode shapes, and mode shape curvature. This paper examines the use of beam-like structures with piezoceramic sensors and actuators to perform identification of those physical parameters, and detect the damage. Experimental results are presented from tests on cantilevered composite beams damaged at different locations and different dimensions. It is demonstrated that the method can sense the presence of damage and obtain the position of a damage.

Nonlinear effects on motions and loads using an iterative time-frequency solver

  • Bruzzone, Dario;Gironi, C.;Grasso, A.
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.3 no.1
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    • pp.20-26
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    • 2011
  • A weakly nonlinear seakeeping methodology for predicting motions and loads is presented in this paper. This methodology assumes linear radiation and diffraction forces, calculated in the frequency domain, and fully nonlinear Froude-Krylov and hydrostatic forces, evaluated in the time domain. The particular approach employed here allows to overcome numerical problems connected to the determination of the impulse response functions. The procedure is divided into three consecutive steps: evaluation of dynamic sinkage and trim in calm water that can significantly influence the final results, a linear seakeeping analysis in the frequency domain and a weakly nonlinear simulation. The first two steps are performed employing a three-dimensional Rankine panel method. Nonlinear Froude-Krylov and hydrostatic forces are computed in the time domain by pressure integration on the actual wetted surface at each time step. Although nonlinear forces are evaluated into the time domain, the equations of motion are solved in the frequency domain iteratively passing from the frequency to the time domain until convergence. The containership S175 is employed as a test case for evaluating the capability of this methodology to correctly predict the nonlinear behavior related to wave induced motions and loads in head seas; numerical results are compared with experimental data provided in literature.

Desing and Analysis of Weather/Wave Observation Network for the Coastal Zone (연안해역의 기상${\cdot}$파랑관측망 설계 및 해석기술의 구축 - 해양파랑관측자료의 해석방법 -)

  • Ryu Cheong-Ro;KIM Hee-Joon;SHON Byung-Kyu
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.30 no.1
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    • pp.16-30
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    • 1997
  • Application of digital filter to the wave analysis is studied using the observed data by wave gauge. Sea wave data obtained from wave gauge always include long wave frequency components. In order to estimate the sea wave parameters, we must re-analyzed wave data by using a digital filter and the concept of mean sea level correction method. By the wave by wave analysis and spectral methods, sea wave parameters on the basis of wave data obtained by the conventional method and digital filter are compared. The best-fitted design filter determined by the necessary conditions of frequency responses, can be obtained by calculating various transfer functions. Thus, to get the best the digital filter design, both Butterworth filter and Savitzky-Golay filter of digital filter are used in the frequency and time domain, respectively. Three cases of observation wave data are calculated by applying digital filter. The components of different frequency bands in the surf zone are coexisted in three cases. The wave data for wind wave components is computed using the digital filter the surf zone and off-surf zone, and based on the filtered data, wave parameters are calculated by the spectral analysis and wave by wave analysis methods, respectively. As a results, when sea wave data observed by wave gauge are analyzed, the Savitzky-Golay method is recommended which can well appear cut-off frequency by experimental choosing filter length in the time domain. The better mean sea level correction method is the Butterworth filter in the frequency domain.

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Analysis of nursing activities in ambulatory units of secondary and tertiary hospitals (종합병원${\cdot}$종합전문요양기관의 외래 간호활동 분석 연구)

  • Sung, Young-Hee;Park, Jeong-Sook
    • Journal of Korean Academy of Nursing Administration
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    • v.9 no.1
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    • pp.5-18
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    • 2003
  • Purpose : For improvement of nursing services in ambulatory unit, ambulatory nursing activity was identified and the required time by nursing activity was measured. Method : The data were collected from 4 tertiary hospitals and 2 secondary hospitals. The method of data collection was used the self-reporting method. The 123 nurse-work days and 137 nurse-aid-work days in 6 hospitals were analyzed. Results : As a result, 11 ambulatory nursing domains and 79 ambulatory nursing activities were confirmed. Above 50% of subjects performed the general outpatient affair domain. The percentage of total time spent in each domain were as follows : general outpatient affair domain, 58.3%, patient education ${\cdot}$ counseling domain, 10.8%, therapeutic care domain, 8.6% and so on. And the average hours were measured by activity and domain. Conclusion : For the improvement of ambulatory nursing care, the strategies that keep the legal standard of number of ambulatory nurse and exchange the nursing-aid for the nurse is needed. And it is also needed to standardize the ambulatory nursing services.

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A Study on Automation of Big Data Quality Diagnosis Using Machine Learning (머신러닝을 이용한 빅데이터 품질진단 자동화에 관한 연구)

  • Lee, Jin-Hyoung
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.75-86
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    • 2017
  • In this study, I propose a method to automate the method to diagnose the quality of big data. The reason for automating the quality diagnosis of Big Data is that as the Fourth Industrial Revolution becomes a issue, there is a growing demand for more volumes of data to be generated and utilized. Data is growing rapidly. However, if it takes a lot of time to diagnose the quality of the data, it can take a long time to utilize the data or the quality of the data may be lowered. If you make decisions or predictions from these low-quality data, then the results will also give you the wrong direction. To solve this problem, I have developed a model that can automate diagnosis for improving the quality of Big Data using machine learning which can quickly diagnose and improve the data. Machine learning is used to automate domain classification tasks to prevent errors that may occur during domain classification and reduce work time. Based on the results of the research, I can contribute to the improvement of data quality to utilize big data by continuing research on the importance of data conversion, learning methods for unlearned data, and development of classification models for each domain.

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Determination of Vibration Parameters Using The Improved Time Domain Modal Identification Algorithm (개선된 시간영역 해석기법에 의한 동특성 추정)

  • Jung, Beom-Seok
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.3 no.2
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    • pp.147-154
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    • 1999
  • A new approach to conducting the vibration parameters identification algorithm is proposed. The approach employs the concept of modal amplitude ratio implemented in a mode shape estimation. The accuracy of the improved Ibrahim Time Domain identification algorithm in extracting structural modal parameters from free response functions has been studied using computer simulated data for 9 stations on the two-span continuous beam. Simulated responses from the lumped and distributed parameter system demonstrate that this algorithm produces excellent results, even in the 300% noise response.

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Stabilization of Nonlinear Discrete-Time Systems in a Frequency Domain

  • Okuyama, Yoshifumi;Nakamori, Kenji;Takemori, Fumiaki
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.33.2-33
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    • 2001
  • The robust stability condition for sampled-data control systems with a sector nonlinearity was presented in our previous paper. Although it is applicable only to the sampled-data control system of a certain class, a usual discretetime control system can belongs to this type of class. This paper analyzes the amplitude dependent behavior of nonlinear sampled-data (i.e., discrete-time) control systems in a frequency domain. By considering restricted areas (sectors) in the nonlinear characterisitic, the existence of a sustained oscillation is estimated, and the relationship between the stable/unstable conditions and the result derived from describing function is compared. Based on these considerations, the stabilization of nonlinear discrete-time control systems is examined in the frequency domain.

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