Using JavaScript to Study the Stability of Time-Varying ARMA Models

نویسندگان

  • Paul Bouthellier
  • Saeed Dubas
چکیده

In undergraduate (and graduate) courses, when ARMA models are studied, the timeinvariant case is usually considered-where the coefficients of the systems are constant functions of time. In this paper, a program is written to allow students to study the stability of such systems where there are perturbations in the coefficients-thus creating a time-varying system. The bounded-input bounded-output (BIBO) stability of the system will be studied by observing the output of the system and well as computing the timevarying zeros [1], [2] of the system.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust stability of stochastic fuzzy impulsive recurrent neural networks with\ time-varying delays

In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

متن کامل

Comparative Study Among Different Time Series Models for Monthly Rainfall Forecasting in Shiraz Synoptic Station, Iran

In this research, monthly rainfall of Shiraz synoptic station from March 1971 to February 2016 was studied using different time series models by ITSM Software. Results showed that the ARMA (1,12) model based on Hannan-Rissanen method was the best model which fitted to the data. Then, to assess the verification and accuracy of the model, the monthly rainfall for 60 months (from March 2011 to Feb...

متن کامل

Modeling and Forecasting Iranian Inflation with Time Varying BVAR Models

This paper investigates the forecasting performance of different time-varying BVAR models for Iranian inflation. Forecast accuracy of a BVAR model with Litterman’s prior compared with a time-varying BVAR model (a version introduced by Doan et al., 1984); and a modified time-varying BVAR model, where the autoregressive coefficients are held constant and only the deterministic components are allo...

متن کامل

Evaluation of Univariate, Multivariate and Combined Time Series Model to Prediction and Estimation the Mean Annual Sediment (Case Study: Sistan River)

Erosion, sediment transport and sediment estimate phenomenon with their damage in rivers is a one of the most importance point in river engineering. Correctly modeling and prediction of this parameter with involving the river flow discharge can be most useful in life of hydraulic structures and drainage networks. In fact, using the multivariate models and involving the effective other parameter...

متن کامل

Hourly Wind Speed Prediction using ARMA Model and Artificial Neural Networks

In this paper, a comparison study is presented on artificial intelligence and time series models in 1-hour-ahead wind speed forecasting. Three types of typical neural networks, namely adaptive linear element, multilayer perceptrons, and radial basis function, and ARMA time series model are investigated. The wind speed data used are the hourly mean wind speed data collected at Binalood site in I...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006