This paper reports the feasibility of the ARMA model to describe a bursty video source transmitting over a AAL5 ATM link (VBR traffic). The traffic represents the activity of the action movie "Lethal Weapon 3" transmitted over the ATM network using the Fore System AVA-200 ATM video codec with a peak rate of 100 Mbps and a frame rate of 25. The model parameters were estimated for a single video ...

In this paper, we purpose a theoretical development of a metric for speech classification based on cepstral features obtained from ARMA models. Thus working with an ARMA model as a complex rational function, is possible to define a metric d(M,M´) between two stable ARMA models M, M´by means of the cepstrum coefficients of the models. This metric may be calculated algorithmically as a finite sum...

BACKGROUND Acinetobacter baumannii strains co-producing carbapenemase and 16S rRNA methylase are highly resistant to carbapenems and aminoglycosides. METHODS Ninety-three isolates of multidrug-resistant A. baumannii were obtained from an intensive care unit in a hospital in Vietnam. Antimicrobial susceptibility tests and whole genome sequencing were performed. Multilocus sequence typing and t...

We express the classic ARMA time-series model as a directed graphical model. In doing so, we find that the deterministic relationships in the model make it effectively impossible to use the EM algorithm for learning model parameters. To remedy this problem, we replace the deterministic relationships with Gaussian distributions having a small variance, yielding the stochastic ARMA (σARMA) model....

The time domain solution of the equations of motion of structures subjected to a stochastic wind field is often obtained by a step-by-step integration approach. The loading is described by simulated time histories of the aerodynamic force. Recently, autoregressive and moving average (ARMA) recursive models have been utilized to simulate the time series of wind loads. Based on the system dynamic...

In this paper we address the problem of predicting a time series using the ARMA (autoregressive moving average) model, under minimal assumptions on the noise terms. Using regret minimization techniques, we develop effective online learning algorithms for the prediction problem, without assuming that the noise terms are Gaussian, identically distributed or even independent. Furthermore, we show ...

In this paper, we propose an adaptive IIR equalizer based on prefiltering techniques. The proposed equalizer has a cascade structure of an ARMA prefilter and an adaptive FIR equalizer. The ARMA prefilter is designed based on the transfer function estimated by the gradient-type instrumental variable algorithm. Simulation results are shown to confirm the performance of the proposed adaptive IIR e...