• Title/Summary/Keyword: RLS method

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Model Parameter Based Fault Detection for Time-series Data (시계열을 따르는 공정데이터의 모델 모수기반 이상탐지)

  • Park, Si-Jeo;Park, Cheong-Sool;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of the Korea Society for Simulation
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    • v.20 no.4
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    • pp.67-79
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    • 2011
  • The statistical process control (SPC) assumes that observations follow the particular statistical distribution and they are independent to each other. However, the time-series data do not always follow the particular distribution, and most of cases are autocorrelated, therefore, it has limit to adopt the general SPC in tim series process. In this study, we propose a MPBC (Model Parameter Based Control-chart) method for fault detection in time-series processes. The MPBC builds up the process as a time-series model, and it can determine the faults by detecting changes parameters in the model. The process we analyze in the study assumes that the data follow the ARMA (p,q) model. The MPBC estimates model parameters using RLS (Recursive Least Square), and $K^2$-control chart is used for detecting out-of control process. The results of simulations support the idea that our proposed method performs better in time-series process.

Speech Enhancement Using the Adaptive Noise Canceling Technique with a Recursive Time Delay Estimator (재귀적 지연추정기를 갖는 적응잡음제거 기법을 이용한 음성개선)

  • 강해동;배근성
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.7
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    • pp.33-41
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    • 1994
  • A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

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A Study on Real-Time Inertia Estimation Method for STSAT-3 (과학기술위성 3호 실시간 관성모멘트 추정 기법 연구)

  • Kim, Kwangjin;Lee, Sangchul;Oh, Hwa-Suk
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.20 no.4
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    • pp.1-6
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    • 2012
  • The accurate information of mass properties is required for the precise control of the spacecraft. The mass properties, mass and inertia, are changeable by some reasons such as consumption of propellant, deployment of solar panel, sloshing, environmental effect, etc. The gyro-based attitude data including noise and bias reduces the control accuracy so it needs to be compensated for improvement. This paper introduces a real-time inertia estimation method for the attitude determination of STSAT-3, Korea Science Technology Satellite. In this method we first filter the gyro noise with the Extended Kalman Filter(EKF), and then estimate the moment of inertia by using the filtered data from the EKF based on the Recursive Least Square(RLS).

A comparative Study of Noise Prediction Method for Road Traffic Noise Map -Focused on Foreign Traffic Noise Prediction Method- (소음지도 제작을 위한 도로교통 소음예측식 비교연구 -국외 예측식을 중심으로-)

  • Jang, Hwan;Bang, Min;Kim, Heung-Sik
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2008.11a
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    • pp.709-714
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    • 2008
  • The various computer programs are used in computer simulation of the traffic noise prediction. But the difference or problem of calculation method used for road traffic noise prediction is not exactly investigated. In this paper, Road traffic noise is predicted on the specific regions by using four prediction methods such as XPS31-133 model(France), RLS-90 model(Germany), ASJ RTN model(Japan) and FHWA model(U.S.A.), which are operated by a program named SoundPLAN, a program to predict road traffic noise. Those prediction values are compared with a measurement value. The results show that four prediction values for taraffic noise are a little different, because of various input factors according to the prediction methods.

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Real- Time Estimation of the Ventricular Relaxation Time Constant

  • Chun Honggu;Kim Hee Chan;Sohn Daewon
    • Journal of Biomedical Engineering Research
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    • v.26 no.2
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    • pp.87-93
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    • 2005
  • A new method for real-time estimating left ventricular relaxation time constant (T) from the left ventricular (LV) pressure waveform, based on the isovolumic relaxation model, is proposed. The presented method uses a recursive least squares (RLS) algorithm to accomplish real-time estimation. A new criterion to detect the end-point of the isovolumic relaxation period (IRP) for the estimation of T is also introduced, which is based on the pattern analysis of mean square errors between the original and reconstructed pressure waveforms. We have verified the performance of the new method in over 4,600 beats obtained from 70 patients. The results demonstrate that the proposed method provides more stable and reliable estimation of τ than the conventional 'off-line' methods.

Multichannel Blind Equalization using Multistep Prediction and Adaptive Implementation

  • Ahn, Kyung-Seung;Hwang, Ho-Sun;Hwang, Tae-Jin;Baik, Heung-Ki
    • Proceedings of the IEEK Conference
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    • 2001.06a
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    • pp.69-72
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    • 2001
  • Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequence, nor does it require a priori channel information. Recently, Tong et al. proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the second order statistics techniques, fur example, subspace method, prediction error method, and so on. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind equalizer length mismatch as well as for its simple adaptive filter implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary delay. In this paper, we induce the optimal delay, and propose the adaptive blind equalizer with multi-step linear prediction using RLS-type algorithm. Simulation results are presented to demonstrate the proposed algorithm and to compare it with existing algorithms.

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Determination of Probable Rainfall Intensity Formulas for Designing Storm Sewer Systems at Incheon District (우수거 설계를 위한 인천지방에서의 확률강우강도식의 산정)

  • Ahn, Tae-Jin;Kim, Kyung-Sub
    • Journal of Korean Society of Water and Wastewater
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    • v.12 no.3
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    • pp.99-106
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    • 1998
  • This paper presents a procedure for determining the design rainfall depth and the design rainfall intensity at Incheon city area in Korea. In this study the eight probability distributions are considered to estimate the probable rainfall depths for 11 different durations. The Kolmogorov - Smirnov test and the Chi-square test are adopted to test each distribution. The probable rainfall intensity formulas are then determined by i) the least squares (LS) method, ii) the least median squares (LMS) method, iii) the reweighted least squares method based on the LMS (RLS), and iv) the constrained regression (CR) model. The Talbot, the Sherman, the Japanese, and the Unified type are considered to determine the best type for the Incheon station. The root mean squared (RMS) errors are computed to test the formulas derived by four methods. It is found that the Unified type is the most reliable and that all methods presented herein are acceptable for determining the coefficients of rainfall intensity formulas from an engineering point of view.

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An Innovative Application Method of Monthly Load Forecasting for Smart IEDs

  • Choi, Myeon-Song;Xiang, Ling;Lee, Seung-Jae;Kim, Tae-Wan
    • Journal of Electrical Engineering and Technology
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    • v.8 no.5
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    • pp.984-990
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    • 2013
  • This paper develops a new Intelligent Electronic Device (IED), and then presents an application method of a monthly load forecasting algorithm on the smart IEDs. A Multiple Linear Regression (MLR) model implemented with Recursive Least Square (RLS) estimation is established in the algorithm. Case Study proves the accuracy and reliability of this algorithm and demonstrates the practical meanings through designed screens. The application method shows the general way to make use of IED's smart characteristics and thereby reveals a broad prospect of smart function realization in application.

A Study the On-Line Systems Identification of Unknown Systems using Laguerre Models (Laguerre 모델을 이용한 미지 시스템의 온-라인 시스템 동정에 관한 연구)

  • O, Hyeon-Cheol;Kim, Yun-Sang;Lee, Jae-Chun;An, Du-Su
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.6
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    • pp.728-734
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    • 1999
  • An on-line system identification scheme of unknown system is proposed based on a Laguerre models representation. The unknown parameters are detemined using recursive least-square identification. The proposed method have the advantage that an unknown system can be modelled without structural knowledge and assumption about the true model order and time delay. Therefore, the proposed method can make the design procedure very when compared to widely-used conventional method.

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A New Method for Antimicrobial Susceptibility Testing of Vitro-cultured Bacteria by Means of Resonance Light Scattering Technique

  • Shi, Yu-Jun;Chen, Jun;Xu, Ming
    • Journal of Microbiology and Biotechnology
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    • v.18 no.1
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    • pp.118-123
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    • 2008
  • A new method for antimicrobial susceptibility testing of vitro-cultured bacteria on an ordinary fluorescence spectrometer was developed. The viable bacteria reduced 3-(4,5 dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) to produce insoluble particles that displayed intense resonance scattering light. The assay showed a linear relationship between the number of viable bacteria and the intensity of resonance scattering light. Dead bacteria were unable to reduce MTT. Methicillin-resistant Staphylococcus aureus exposed to flavonoids from Marchantia convoluta showed a flavonoids concentration-dependent inhibition of the ability to reduce MTT. In the assay, less than 12 h was required to attain susceptibility results and fewer bacteria were utilized than in traditional methods. The RLS technique could, in combination with the MTT assay, be a rapid and sensitive measuring method to determine the in vitro activity of new antimicrobials.