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Convergence and power spectrum density of ARIMA model and binary signal

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We study the weak convergence of various models to Fractional Brownian motion. First, we consider arima process and ON/OFF source model which allows for long packet trains and long inter-train distances. Finally, we figure out power spectrum density as a Fourier transform of autocorrelation function of arima model and binary signal model.

Abstract

We study the weak convergence of various models to Fractional Brownian motion. First, we consider arima process and ON/OFF source model which allows for long packet trains and long inter-train distances. Finally, we figure out power spectrum density as a Fourier transform of autocorrelation function of arima model and binary signal model.

참고문헌 (9)

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  7. G. Samorodnitsky, "Stable non-Gaussian processes: Stochastic models with Innite Variance" (1994), Chapman and Hall
  8. M. S. Taqqu, "Estimators for long-range depen-dence : Empirical study", Fractals, 3(4), pp.785~798 (1995)
  9. M. S. Taqqu, "Proof of a fundamental result in self-similar tracffic modeling", Computer Communication review, ~ (1997)

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