A novel time series analysis is presented to locate damage sources in a mechanical system, which is running in various operational environments. The source of damage is located by solely analyzing the acceleration time histories recorded from a structure of interest. First, a data normalization procedure is proposed. This procedure selects a reference signal that is ‘closest’ to a newly obtaine...

This paper gives an example of an auto-regressive (AR) spectral analysis on transient musical sounds. The attack part of many musical sounds is mostly too short to be analysed by a short-time Fourier analysis, whereas this short period of time is long enough for several AR-methods. The AR-spectra obtained from short segments of signals with attack transients have a sufficiently high frequency r...

In this study, it was investigated to what extent linear auto regressive models with external input (ARX) and auto regressive moving average models with external input (ARMAX) could be used to describe the inside air temperature of an unheated, naturally ventilated greenhouse under Western European conditions. Outside air temperature and relative humidity, global solar radiation, and cloudiness...

there are two main reasons for studying investment in an economy. first, the combination of firms? investment demand and household?s saving supply determines how much of an economys? resoures is invested. second, investment is highly volatile; thus investment demand may be important in the short-run fluctuations. the present article examins the relationship and veracity of existence of banks pr...

| The temporal structure of the force, or strain, signals from an internal force-torque sensor can be a rich source of information about robot/environment contact conditions. We present a procedure for representing and segmenting the individual signals with an auto-regressive model. This procedure produces segments of approximately constant spectrum, and is a powerful technique for detecting ab...

We discuss the classic auto regressive statistical models Box and Jenkins used in prediction problems, and their application is analyzed in the energy sector. Subsequently, we propose a methodology based on the application of these models for the prediction of electric power generation, from data obtained at a wind farm in Ventosa, Oaxaca. Finally, the model and the preliminary results obtained...

This study intends to examine the influence of trade openness on economic growth in Kingdom Saudi Arabia including government consumption and labor force as control variables. Using time-series yearly data from 1985 2019, applies Auto-Regressive Distributed Lag (ARDL) cointegration regression Toda-Yamamoto (T-Y) Granger causality check achieve objective study. The ARDL model estimation disclose...

This paper proposes a stochastic multipath model useful for generating MIMO channel matrices in timevariant environments. The multipath model is developed by first extracting the relevant characteristics from measured indoor channel data and subsequently capturing these characteristics in an auto-regressive stochastic model. This model is then used to generate channel matrices whose space-time ...

BACKGROUND Outbreaks of hand-foot-mouth disease (HFMD) have been reported for many times in Asia during the last decades. This emerging disease has drawn worldwide attention and vigilance. Nowadays, the prevention and control of HFMD has become an imperative issue in China. Early detection and response will be helpful before it happening, using modern information technology during the epidemic....

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.