This paper presents a robust receiver for uplink directsequence code-division multiple access (DS-CDMA) systems. The receiver uses low order auto-regressive models to approximate the multi-path fading channel taps, and a post correlation-based uncertain model for estimation purposes. keywords: RAKE receiver, Kalman filter, robust filter, multipath fading, multiuser detection.

Stochastic, processes can be stationary or nonstationary. They depend on the magnitude of shocks. In other words, in an auto regressive model of order one, the estimated coefficient is not constant. Another finding of this paper is the relation between estimated coefficients and residuals. We also develop a catastrophe and chaos theory for change of roots from stationary to a nonstationary one ...

In business, industry and government agencies, anticipating future behavior that involves many critical variables for nation wealth creation is vitally important, thus the necessity to make precise decision by the policy makers is really essential. Consequently, an accurate and reliable forecast system is needed to compose such predictions. Accordingly, the aim of this research is to develop a ...

The application of multivariate time series is so large,it can be used in many systems, like ecnomic systems,biological systems, and so on.This paper introduced the method’s building and the structure of ARIMAX model (auto-regressive integrated moving average model with explanatory variables) and its SAS realizing. The paper analysed the tertiaryindustry in China with the realty business to be ...

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...

Earned value management (EVM) is a well-known approach in a project control system which uses some indices to track schedule and cost performance of a project. In this paper, a new statistical framework based on self-starting monitoring and change point estimation is proposed to monitor correlated EVM indices which are usually auto-correlated over time and non-normally distributed. Also, a new ...

Periodically stationary times series are useful to model physical systems whose mean behavior and covariance structure varies with the season. The Periodic Auto-Regressive Moving Average (PARMA) process provides a powerful tool for modelling periodically stationary series. Since the process is non-stationary, the innovations algorithm is useful to obtain parameter estimates. Fitting a PARMA mod...

this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects th...

We present a comparative study of electricity consumption predictions using the SARIMAX method (Seasonal Auto Regressive Moving Average eXogenous variables), HyFis2 model (Hybrid Neural Fuzzy Inference System) and LSTNetA (Long Short Time series Network Adapted), hybrid neural network containing GRU (Gated Recurrent Unit), CNN (Convolutional Network) dense layers, specially adapted for this cas...