This paper deals with the approximation of a given frequency response by a low-order linear ARMA filter (Auto-Regressive Moving Average). The aim of this work is the audio synthesis, then to improve the perceptual quality, a criterion based on human listening is defined and minimized. Two complementary approaches are proposed here for solving this non-linear and non-convex problem: first, a wei...

short-term traffic flow forecasting plays a significant role in the intelligent transportation systems (its), especially for the traffic signal control and the transportation planning research. two mainly problems restrict the forecasting of urban freeway traffic parameters. one is the freeway traffic changes non-regularly under the heterogeneous traffic conditions, and the other is the success...

I will report on a study of the usefulness of ARMA time scale algorithms to synchronize clocks on a digital network. The algorithm acquires periodic time differences between a local system clock and a remote time server by means of any of the standard message formats such as the format used by the Network Time Protocol. It models the current time difference as a linear combination of previous t...

To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observatio...

It is essential to find solar predictive methods to massively insert renewable energies on the electrical distribution grid. The goal of this study is to find the best methodology allowing predicting with high accuracy the hourly global radiation. The knowledge of this quantity is essential for the grid manager or the private PV producer in order to anticipate fluctuations related to clouds occ...

In the neurological intensive care unit (NICU), prediction of impending changes in patient condition would be highly beneficial. In this paper, we employ a neuro-fuzzy inference system (NFIS) for short-term prediction of heart rate variability in the NICU. An NFIS was selected because it allows for a "gray-box" approach through which a system identification procedure is used in conjunction with...

In this study we have analysed wind and wave time series data resulting from hourly measurements on the sea surface in Bushehr, the northern part of the Persian Gulf, from 15 July to 4 August 2000. Wind speed (U10) ranged from 0.34 to 10.38 m/s as alternating sea and land breezes. The lowest wind speed occurs at about midnight and the highest at around noon. The calculated autocorrelation of wi...

In today’s world, using quantitative methods are very important for financial markets forecast, improvement of decisions and investments. In recent years, various time series forecasting methods have been proposed for financial markets forecasting. In each case, the accuracy of time series methods fundamental to make decision and hence the research for improving the effectiveness of forecasting...

C. L. Wu and K. W. Chau* 2 Dept. of Civil and Structural Engineering, Hong Kong Polytechnic University, 3 Hung Hom, Kowloon, Hong Kong, People’s Republic of China 4 5 *Email: [email protected] 6 ABSTRACT 7 Data-driven techniques such as Auto-Regressive Moving Average (ARMA), K-Nearest-Neighbors (KNN), and 8 Artificial Neural Networks (ANN), are widely applied to hydrologic time series predi...