• Title/Summary/Keyword: nonstationary simulation

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A Neural Multiple LMS Based ANC System for Reducing Acoustic Noise of High-Speed Trains (신경회로망 다중 LMS 기법을 이용한 고속철도의 실내소음저감을 위한 ANC 시스템)

  • Cho, Hyun-Cheol;Lee, Kwon-Soon;Nam, Hyun-Do
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.4
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    • pp.385-390
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    • 2009
  • This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

Near Lossless Medical Image Compression using Wavelet Transform (웨이블릿변환을 이용한 무손실에 가까운 의료영상압축)

  • Yoon, Ki-Byung;Ahn, Chang-Beom
    • Proceedings of the KOSOMBE Conference
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    • v.1995 no.11
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    • pp.113-116
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    • 1995
  • Medical image compression using the wavelet transform has been tried. Due to the flexibility in representing nonstationary image signal in both time and frequency domains and its ability to adapt human visual characteristics, wavelet transform has unique advantage in images compression. In the proposed wavelet compression original image is decomposed into multi-scale bands. Different scale factors are employed in the quantization of wavelet decomposed images in different bands. For the lowest band, a predictor is designed and error signal is entropy coded. For high scale bands, runlength coding for toro run is used with Huffman coding. From simulation with magnetic resonance images($256\times256$ size, 256 graylevels) the proposed algorithm is superior to the JPEG by more than 2.5 dB in near lossless compression (CR = 8 - 10).

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A Study of the Compression for the Power Quality Disturbance Signal by using the Phase Estimation of Stationary Signal (정상신호의 위상 추정을 이용한 전력 품질 왜곡 신호의 압축에 관한 연구)

  • Chung, Young-Sik;Park, Chan-Woong
    • Proceedings of the KIEE Conference
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    • 2005.07a
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    • pp.341-343
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    • 2005
  • This paper introduces a compression algorithm for power quality disturbance signal via the discrete wavelet transform, DWT. Algorithm to estimate a time delay from the power quality disturbance signal is proposed. Pseudo-stationary signal is constructed from the estimated time delay. A difference signal or nonstationary signal is obtained by removing a pseudo-stationary signal from a disturbance signal. DWT is applied to a difference signal. The threshold is applied to reduce a number of coefficients. Simulation results show the resonable compression ratio while keep low signal distortion.

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A Study on the Analysis of Stochastic Nonlinear Dynamic System (확률적 비선형 동적계의 해석에 관한 연구)

  • 남성현;김호룡
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.3
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    • pp.697-704
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    • 1995
  • The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents the stochastic model of a nonlinear dynamic system with uncertain parameters under nonstationary stochastic inputs. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method and the second moment equation is numerically evaluated by stochastic process closure method, 4th cumulant neglect closure method and Runge-Kutta method. But the first and the second moment equations are coupled each other, so this equations are approximately evaluated by a iterative method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

Analysis of the Antenna Pointing Instability of a Satellite in Spin-Stabilized Injection Mode

  • Kang, Ja-Young;Shin, Kwang-Keun
    • ETRI Journal
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    • v.16 no.2
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    • pp.27-41
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    • 1994
  • A new mathematical model to predict the beam pointing instability of a nonconservative two-body satellite system in spinning injection mode has been developed by using Newton-Euler and projection methods. Since the on-axis and null axis of the omni antenna with toroidal pattern beam form a right angle, wobbling of the antenna on-axis is measured by determining the Euler angles which represent the orientation of the satellite's spin axis. Because of the complexity of the system which is a time varying, nonstationary, nonlinear dynamical system, a numerical method is used for the analysis. Computer simulation results present the effects of the mass distribution and internal mass motion on the antenna beam pointing.

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Online Learning Control for Network-induced Time Delay Systems using Reset Control and Probabilistic Prediction Method (네트워크 기반 시간지연 시스템을 위한 리세트 제어 및 확률론적 예측기법을 이용한 온라인 학습제어시스템)

  • Cho, Hyun-Cheol;Sim, Kwang-Yeul;Lee, Kwon-Soon
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.9
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    • pp.929-938
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    • 2009
  • This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

Nonstationary Markov Chain Model for Multi-site Daily Rainfall Simulation (비정상성 Markov Chain Model을 이용한 다지점 일강수량 모의)

  • Moon, Jang-Won;Kwon, Hyun-Han;Moon, Young-Il
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.1495-1499
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    • 2010
  • 최근에 기후변화 영향 분석을 위한 강수모의발생 기법에 대한 연구가 중요한 문제로 대두되고 있다. 기본적으로 모의된 강수량이 유역단위에서 의미 있는 값으로 수문모형에 입력자료로 활용되기 위해서는 강수지점간의 공간상관성의 유지가 매우 중요하다. 즉 지역적인 수문학적 거동을 유역단위에서 평가하기 위해서는 유역상관성을 고려할 수 있는 다지점(multisite) 모형의 개발이 필수적이다. 이러한 점에서 본 연구에서는 다지점 강수모의기법을 개발하였으며 비정상성 해석이 가능하도록 동역학적 강수모형을 구성하였다. 이를 한강유역 강수지점에 적용하여 모형의 적합성을 평가하였다.

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An Adaptive Digital Notch Filter for Stabilization of Single-Phase Grid-Connected Inverters With LCL Filter (LCL 필터가 결합된 단상 계통연계형 인버터의 안정화를 위한 적응형 디지털 노치 필터)

  • Heo, Jin-Yong;Kim, Hak-Soo;Nho, Eui-Cheol
    • The Transactions of the Korean Institute of Power Electronics
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    • v.26 no.5
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    • pp.307-314
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    • 2021
  • Even though the LCL filters have superior harmonic attenuation ability to L filters, stability has always been an issue. The system could be unstable because of the resonance phenomenon, especially when digital controller is used. Adding a notch filter to the compensator is one approach to solve the problem. Resonance phenomenon can be inhibited by aligning notch frequency to system resonance frequency. However, resonance frequency variation can be obtained because the actual system has a nonstationary characteristic. Therefore, the system could be unstable, where the system parameters are changed when the conventional notch filter is used. An adaptive digital notch filter that stabilizes the system even system parameters are changed. Simulation and experiment results are provided to verify the validity of the proposed adaptive filter.

Effects of incorrect detrending on the coherency between non-stationary time series processes

  • Lee, Jin
    • Communications for Statistical Applications and Methods
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    • v.26 no.1
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    • pp.27-34
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    • 2019
  • We study the effect of detrending on the coherency between two time series processes. Many economic and financial time series variables include nonstationary components; however, we analyze the two most popular cases of stochastic and deterministic trends. We analyze the asymptotic behavior of coherency under incorrect detrending, which includes the cases of first-differencing the deterministic trend process and, conversely, the time trend removal of the unit root process. A simulation study is performed to investigate the finite sample performance of the sample coherency due to incorrect detrending. Our work is expected to draw attention to the possible distortion of coherency when the series are incorrectly detrended. Further, our results can extend to various specification of trends in aggregate time series variables.

A Study on the Analysis of Stochastic Dynamic System (확률적 동적계의 해석에 관한 연구)

  • Nam, S.H.;Kim, H.R.
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.4
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    • pp.127-134
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    • 1995
  • The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents a generalized stochastic model of dynamic system subjected to bot external and parametric nonstationary stochastic input. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method. But the second moment equation is founded to constitute an infinite coupled set of differential equations, so this equations are numerically evaluated by cumulant neglect closure method and Runge-Kutta method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

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