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The composite vector stochastic processes model is usable in many signal processing areas. Advantages of the model utilization, in task of electric motors acoustic signals parametric estimations, are shown in this paper. Models' results are compared with the traditional statistical methods for the signal analysis, in the two samples classes recognition task. The expressions for correlation function,...
Inflation forecasts becomes a key input of monetary policy decision. CPI is a measure of inflation, however, an important economic indicator. Based on the monthly CPI data from January 2000 to December 2009, the thesis firstly statistically indentifies the correlation function and the partial correlation function of consumer price index, tests the stationarity of ADF, then uses ARIMA model to test...
In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially moving window method and correlation function. The main purpose of this paper is to prevent damage or crack from the fatigue in advance. In this paper 16 channel sensor data are considered and each sensor frequency is 100 Hz and sampling...
In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially moving window method and correlation function. The main purpose of this paper is to prevent damage or crack from the fatigue in advance. In this paper 16 channel sensor data are considered and each sensor frequency is 100 Hz and sampling...
The problem of identification of the modal parameters of a structural model using measured ambient response time histories is addressed. A Bayesian time-domain approach for modal updating is presented which is based on an approximation of a conditional probability expansion of the response. It allows one to obtain not only the optimal values of the updated modal parameters but also their associated...
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