• Title/Summary/Keyword: Function Estimation

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An Algorithm of Score Function Generation using Convolution-FFT in Independent Component Analysis (독립성분분석에서 Convolution-FFT을 이용한 효율적인 점수함수의 생성 알고리즘)

  • Kim Woong-Myung;Lee Hyon-Soo
    • The KIPS Transactions:PartB
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    • v.13B no.1 s.104
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    • pp.27-34
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    • 2006
  • In this study, we propose this new algorithm that generates score function in ICA(Independent Component Analysis) using entropy theory. To generate score function, estimation of probability density function about original signals are certainly necessary and density function should be differentiated. Therefore, we used kernel density estimation method in order to derive differential equation of score function by original signal. After changing formula to convolution form to increase speed of density estimation, we used FFT algorithm that can calculate convolution faster. Proposed score function generation method reduces the errors, it is density difference of recovered signals and originals signals. In the result of computer simulation, we estimate density function more similar to original signals compared with Extended Infomax and Fixed Point ICA in blind source separation problem and get improved performance at the SNR(Signal to Noise Ratio) between recovered signals and original signal.

An Accurate Estimation of a Modal System with Initial Conditions (ICCAS 2004)

  • Seo, In-Yong;Pearson, Allan E.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1694-1700
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    • 2004
  • In this paper, we propose the AWLS/MFT (Adaptive Weighed Least Squares/ Modulation Function Technique) devised by A. E. Pearson et al. for the transfer function estimation of a modal system and investigate the performance of several algorithms, the Gram matrix method, a Luenberger Observer (LO), Least Squares (LS), and Recursive Least Squares (RLS), for the estimation of initial conditions. With the benefit of the Modulation Function Technique (MFT), we can separate the estimation problem into two phases: the transfer function parameters are estimated in the first phase, and the initial conditions are estimated in the second phase. The LO method produces excellent IC estimates in the noise free case, but the other three methods show better performance in the noisy case. Finally, we compared our result with the Prony based method. In the noisy case, the AWLS and one of the three methods - Gram matrix, LS, and RLS- show better performance in the output Signal to Error Ratio (SER) aspect than the Prony based method under the same simulation conditions.

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New generalized inverse Weibull distribution for lifetime modeling

  • Khan, Muhammad Shuaib;King, Robert
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.147-161
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    • 2016
  • This paper introduces the four parameter new generalized inverse Weibull distribution and investigates the potential usefulness of this model with application to reliability data from engineering studies. The new extended model has upside-down hazard rate function and provides an alternative to existing lifetime distributions. Various structural properties of the new distribution are derived that include explicit expressions for the moments, moment generating function, quantile function and the moments of order statistics. The estimation of model parameters are performed by the method of maximum likelihood and evaluate the performance of maximum likelihood estimation using simulation.

Reliability in Two Independent Uniform and Power Function-Half Normal Distribution

  • Woo, Jung-Soo
    • Communications for Statistical Applications and Methods
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    • v.15 no.3
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    • pp.325-332
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    • 2008
  • We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.

Estimation of Jump Points in Nonparametric Regression

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.899-908
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    • 2008
  • If the regression function has jump points, nonparametric estimation method based on local smoothing is not statistically consistent. Therefore, when we estimate regression function, it is quite important to know whether it is reasonable to assume that regression function is continuous. If the regression function appears to have jump points, then we should estimate first the location of jump points. In this paper, we propose a procedure which can do both the testing hypothesis of discontinuity of regression function and the estimation of the number and the location of jump points simultaneously. The performance of the proposed method is evaluated through a simulation study. We also apply the procedure to real data sets as examples.

Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing

  • Kim, Myung Joon;Kim, Yeong-Hwa
    • Communications for Statistical Applications and Methods
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    • v.21 no.3
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    • pp.235-243
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    • 2014
  • Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and empirical Bayes estimates produce by matching first and second empirical moments; subsequently, a constrained Bayes estimate is recommended to use in case the research objective is to produce a histogram of the estimates considering the location and dispersion. The well-known squared error loss function exclusively emphasizes the precision of estimation and may lead to biased estimators. Thus, the balanced loss function is suggested to reflect both goodness of fit and precision of estimation. In insurance pricing, the accurate location estimates of risk and also dispersion estimates of each risk group should be considered under proper loss function. In this paper, by applying these two ideas, the benefit of the constrained Bayes estimates and balanced loss function will be discussed; in addition, application effectiveness will be proved through an analysis of real insurance accident data.

ESTIMATION OF NON-INTEGRAL AND INTEGRAL QUADRATIC FUNCTIONS IN LINEAR STOCHASTIC DIFFERENTIAL SYSTEMS

  • Song, IL Young;Shin, Vladimir;Choi, Won
    • Korean Journal of Mathematics
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    • v.25 no.1
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    • pp.45-60
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    • 2017
  • This paper focuses on estimation of an non-integral quadratic function (NIQF) and integral quadratic function (IQF) of a random signal in dynamic system described by a linear stochastic differential equation. The quadratic form of an unobservable signal indicates useful information of a signal for control. The optimal (in mean square sense) and suboptimal estimates of NIQF and IQF represent a function of the Kalman estimate and its error covariance. The proposed estimation algorithms have a closed-form estimation procedure. The obtained estimates are studied in detail, including derivation of the exact formulas and differential equations for mean square errors. The results we demonstrate on practical example of a power of signal, and comparison analysis between optimal and suboptimal estimators is presented.

A Novel Channel Estimation Scheme for OFDM/OQAM-IOTA System

  • Kang, Seung-Won;Chang, Kyung-Hi
    • ETRI Journal
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    • v.29 no.4
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    • pp.430-436
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    • 2007
  • An OFDM/offset QAM (OQAM)-IOTA system uses the isotropic orthogonal transform algorithm (IOTA) function, which has good localization properties in the time and frequency domains. This is employed instead of the guard interval used in a conventional OFDM/QAM system in order to be robust for multi-path channels. However, the conventional channel estimation scheme is not valid for an OFDM/OQAM-IOTA system due to the intrinsic inter-symbol interference of the IOTA function. In this paper, a condition is derived to reduce the intrinsic interference of the IOTA function. This condition is obtained with the proposed pilot structure used for perfect channel estimation. We also derive the preamble structure appropriate for practical channel estimation of the OFDM/OQAM-IOTA system. Simulation results show that the OFDM/OQAM-IOTA system with the proposed preamble structure performs better than the conventional OFDM system, and it has the additional advantage of an increased data transmission rate which corresponds to the guard interval retrieval.

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An Enhanced Function Point Model for Software Size Estimation: Micro-FP Model (소프트웨어 규모산정을 위한 기능점수 개선 Micro-FP 모형의 제안)

  • Ahn, Yeon-S.
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.12
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    • pp.225-232
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    • 2009
  • Function Point Method have been applied to measure software size estimation in industry because it supports to estimate the software's size by user's view not developer's. However, the current function point method has some problems for example complexity's upper limit etc. So, In this paper, an enhanced function point model. Micro FP model, was suggested. Using this model, software effort estimation can be more efficiently because this model has some regression equation. This model specially can be applied to estimate in detail the large application system's size Analysis results show that measured software size by this Micro FP model has the advantage with more correlative between the one of LOC, as of 10 applications operated in an large organization.

Bayes and Empirical Bayes Estimation of the Scale Parameter of the Gamma Distribution under Balanced Loss Functions

  • Rezaeian, R.;Asgharzadeh, A.
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.71-80
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    • 2007
  • The present paper investigates estimation of a scale parameter of a gamma distribution using a loss function that reflects both goodness of fit and precision of estimation. The Bayes and empirical Bayes estimators rotative to balanced loss functions (BLFs) are derived and optimality of some estimators are studied.