• Title/Summary/Keyword: Gaussian Processes

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TRANSLATION THEOREMS FOR THE ANALYTIC FOURIER-FEYNMAN TRANSFORM ASSOCIATED WITH GAUSSIAN PATHS ON WIENER SPACE

  • Chang, Seung Jun;Choi, Jae Gil
    • Journal of the Korean Mathematical Society
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    • v.55 no.1
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    • pp.147-160
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    • 2018
  • In this article, we establish translation theorems for the analytic Fourier-Feynman transform of functionals in non-stationary Gaussian processes on Wiener space. We then proceed to show that these general translation theorems can be applied to two well-known classes of functionals; namely, the Banach algebra S introduced by Cameron and Storvick, and the space ${\mathcal{B}}^{(P)}_{\mathcal{A}}$ consisting of functionals of the form $F(x)=f({\langle}{\alpha}_1,x{\rangle},{\ldots},{\langle}{\alpha}_n,x{\rangle})$, where ${\langle}{\alpha},x{\rangle}$ denotes the Paley-Wiener-Zygmund stochastic integral ${\int_{0}^{T}}{\alpha}(t)dx(t)$.

A generalization of Price's theorem with constrained non-Gaussian inputs (제한적 비가우시안 입력에 대한 Price 정리의 일반화)

  • 방승찬;안승길;송익호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.2
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    • pp.338-344
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    • 1994
  • Price`s theorem is generalized for general zero memory nonlinear function when input are drawn from a sum, called the constrained non-Gaussian, of two or more mutually independent processes of which the first is the Gaussian. An example is given to illustrate the applicability of the generalization.

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A GAUSSIAN WHITE NOISE GENERATOR AND ITS APPLICATION TO THE FLUCTUATION-DISSIPATION FORMULA

  • Moon, Byung-Soo
    • Journal of applied mathematics & informatics
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    • v.15 no.1_2
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    • pp.363-375
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    • 2004
  • In this paper, We show that the bandpass random signals of the form ∑$_{\alpha}$$\alpha$$_{\alpha}$ a Sin(2$\pi$f$_{\alpha}$t + b$_{\alpha}$) where a$_{\alpha}$ being a random number in [0,1], f$_{\alpha}$ a random integer in a given frequency band, and b$_{\alpha}$ a random number in [0, 2$\pi$], generate Gaussian white noise signals and hence they are adequate for simulating Continuous Markov processes. We apply the result to the fluctuation-dissipation formula for the Johnson noise and show that the probability distribution for the long term average of the power of the Johnson noise is a X$^2$ distribution and that the relative error of the long term average is (equation omitted) where N is the number of blocks used in the average.error of the long term average is (equation omitted) where N is the number of blocks used in the average.

Translation method: a historical review and its application to simulation of non-Gaussian stationary processes

  • Choi, Hang;Kanda, Jun
    • Wind and Structures
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    • v.6 no.5
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    • pp.357-386
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    • 2003
  • A number of methods based on various ideas have been proposed for simulating the non-Gaussian stationary process. However, these methods have some limitations. This paper reviewed several simulation methods based on the translation method using logarithmic and polynomial functions, which have emerged in the history of statistics and in the field of civil engineering. The applicability of each method is discussed from the viewpoint of the reproducibility of higher order statistics of the object function in the simulated sample functions, and examined using pressure signals measured from wind tunnel experiments for various shapes of buildings. The parameter estimation methods, i.e. the method of moments and quantile plot, are also reviewed, and the useful aspects of each method are discussed. Additionally, a simple worksheet for parameter estimation is derived based on the method of moment for practical application, and the accuracy is discussed comparing with a set of previously proposed formulae.

Two Sample Test Procedures for Linear Rank Statistics for Garch Processes

  • Chandra S. Ajay;Vanualailai Jito;Raj Sushil D.
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.557-587
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    • 2005
  • This paper elucidates the limiting Gaussian distribution of a class of rank order statistics {$T_N$} for two sample problem pertaining to empirical processes of the squared residuals from two independent samples of GARCH processes. A distinctive feature is that, unlike the residuals of ARMA processes, the asymptotics of {$T_N$} depend on those of GARCH volatility estimators. Based on the asymptotics of {$T_N$}, we empirically assess the relative asymptotic efficiency and effect of the GARCH specification for some GARCH residual distributions. In contrast with the independent, identically distributed or ARMA settings, these studies illuminate some interesting features of GARCH residuals.

Weak Convergence for Nonparametric Bayes Estimators Based on Beta Processes in the Random Censorship Model

  • Hong, Jee-Chang
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.545-556
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    • 2005
  • Hjort(1990) obtained the nonparametric Bayes estimator $\^{F}_{c,a}$ of $F_0$ with respect to beta processes in the random censorship model. Let $X_1,{\cdots},X_n$ be i.i.d. $F_0$ and let $C_1,{\cdot},\;C_n$ be i.i.d. G. Assume that $F_0$ and G are continuous. This paper shows that {$\^{F}_{c,a}$(u){\|}0 < u < T} converges weakly to a Gaussian process whenever T < $\infty$ and $\~{F}_0({\tau})\;<\;1$.

A Fast MSRCR Algorithm Using Hierarchical Discrete Correlation (HDC를 이용한 고속 MSRCR 알고리즘)

  • Han, Kyu-Phil
    • Journal of Korea Multimedia Society
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    • v.13 no.11
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    • pp.1621-1629
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    • 2010
  • This paper presents an improved fast MSRCR algorithm that MSRs are commonly adopted at tone mapping in color vision. Conventional MSRs consist of three SSRs, which use three Gaussian functions with different scales as those surround ones. This convolution processes require much computation load. Therefore, the proposed algorithm adopts a hierarchical discrete correlation which is equivalent to Gaussian function and the Retinex process is only applied to the luminance channel in order to get a fast processing. A simple color preservation scheme is applied to the Retinex output from the luminance channel in the proposed MSRCR algorithm. Experimental results show that the proposed algorithm required less number of oprations and computation time about 1/9.5 and 1/3.5 times, respectively, than those of the simplest MSR and was equivalent to conventional MSRs.

Study on Image Processing Techniques Applying Artificial Intelligence-based Gray Scale and RGB scale

  • Lee, Sang-Hyun;Kim, Hyun-Tae
    • International Journal of Advanced Culture Technology
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    • v.10 no.2
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    • pp.252-259
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    • 2022
  • Artificial intelligence is used in fusion with image processing techniques using cameras. Image processing technology is a technology that processes objects in an image received from a camera in real time, and is used in various fields such as security monitoring and medical image analysis. If such image processing reduces the accuracy of recognition, providing incorrect information to medical image analysis, security monitoring, etc. may cause serious problems. Therefore, this paper uses a mixture of YOLOv4-tiny model and image processing algorithm and uses the COCO dataset for learning. The image processing algorithm performs five image processing methods such as normalization, Gaussian distribution, Otsu algorithm, equalization, and gradient operation. For RGB images, three image processing methods are performed: equalization, Gaussian blur, and gamma correction proceed. Among the nine algorithms applied in this paper, the Equalization and Gaussian Blur model showed the highest object detection accuracy of 96%, and the gamma correction (RGB environment) model showed the highest object detection rate of 89% outdoors (daytime). The image binarization model showed the highest object detection rate at 89% outdoors (night).

A Note on Exponential Inequalities of ψ-Weakly Dependent Sequences

  • Hwang, Eunju;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
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    • v.21 no.3
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    • pp.245-251
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    • 2014
  • Two exponential inequalities are established for a wide class of general weakly dependent sequences of random variables, called ${\psi}$-weakly dependent process which unify weak dependence conditions such as mixing, association, Gaussian sequences and Bernoulli shifts. The ${\psi}$-weakly dependent process includes, for examples, stationary ARMA processes, bilinear processes, and threshold autoregressive processes, and includes essentially all classes of weakly dependent stationary processes of interest in statistics under natural conditions on the process parameters. The two exponential inequalities are established on more general conditions than some existing ones, and are proven in simpler ways.

Mixed Noise Removal using Modified Switching Filter (변형된 스위칭 필터를 이용한 복합잡음 제거)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.397-400
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    • 2016
  • In digital images, the addition due to noise occurs in the process of obtaining, saving, and transmitting. For examples of noise, there are salt and pepper noise, Gaussian noise, and composition noise where various noises are mixed. Existing filters have insufficient noise removal characteristics because it uses single filters in composite noise environment. Therefore the study suggested a switching filter that processes with special weighted value and median filter according to local mask salt and pepper noise density when central pixel is damaged by salt and pepper noise, and processes by applying weighted values differently according to standard deviation of local mask when damaged by Gaussian noise.

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