This paper presents new speech analysis method based on a Glottal-ARMAX (Auto Regressive and Moving Average eXogenous) model with phase compensation. A Glottal-ARMAX model consists of two kinds of inputs: glottal source model excitation and a white gauss input, and a vocal tract ARMAX model. The proposed method can simultaneously estimate the glottal source model and vocal tract ARMAX model par...

Spam has been one of the most difficult problems to be addressed since the invention of Internet. Outbound spam can reflect the information security level of an organization as most spam emails are generated by compromised computers. Understanding the trend of outbound spam can help organizations adopt proactive policies and measures toward a more informed decision on resource allocation in ter...

Streamflow forecasting is very important for water resources management and flood defence. In this paper two forecasting methods are compared: ARIMA versus a multilayer perceptron neural network. This comparison is done by forecasting a streamflow of a Mexican river. Surprising results showed that in a monthly basis, ARIMA has lower prediction errors than this Neural Network. Key-Words: Auto re...

This paper presents a self-organizing power system stabilizer (SOPSS) which use the fuzzy Auto-Regressive Moving Average (FARMA) model. The control rules and the membership functions of proposed the fuzzy logic controller are generated automatically without using any plant model. The generated rules are stored in the fuzzy rule space and updated on-line by a self-organizing procedure. To show t...

The relentless spread of photovoltaic production drives searches smart approaches to mitigate unbalances in power demand and supply, instability on the grid ensuring stable revenues producer. Because development energy markets with multiple time sessions, there is a growing need forecasting for steps, from fifteen minutes up days ahead. To address this issue, study both short-term-horizon three...

Naturally ventilated tropical greenhouse is classified as a complex system because it involves with nonlinear process and multivariable system. The purpose of this study is to determine the mathematical model of NVTG climates to in order to describe and predict the dynamic behavior of temperature and humidity inside NVTG for development of its control system. The modeling of the system is divid...

Improving forecasting especially time series forecasting accuracy is an important yet often difficult task facing forecasters. Fuzzy autoregressive integrated moving average (FARIMA) models are the fuzzy improved version of the autoregressive integrated moving average (ARIMA) models, proposed in order to overcome limitations of the traditional ARIMA models; especially data limitation, and yield...

A time series forecasting is an active research applied significantly in a variety of economics areas. Over the past three decades an auto-regressive integrated moving average (ARIMA) model, as one of the most important time series models, has been applied in financial markets forecasting. Recent researches in time series forecasting ARIMA models indicate some basic limitations which detract fr...

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...