Least Squares Parameters Estimation in Infocommunication Systems
The paper purposes for predicting data trend for calculating infocommunication system’s parameters. As a result, a solution to the problem of determining the changing values of time series is proposed, assuming that it has a linear relationship with another time series in the models of infocommunication systems. Regression analysis is used to determine parameters values from a set of observational data. The paper deals with power and exponential regression. Mathematical modeling programs developed for multiple regression models can be used to test the adequacy of autoregressive models on the basis that the least-squares estimation problems of multiple linear regression parameters do not have significant differences with p-order autoregression. In this case, partial correlations between components of the series with more than five steps apart from each other are equal to zero. The considered methodology is of interest because modern infocommunication systems are complex systems with many states and co-dependencies between them. Therefore, the task of short-term forecasting simulation simplifies the process of finding the parameters. The software implementation of the solution was worked out in Matlab. An experimental method was used to obtain a least squares estimation of the theoretical parameters of models. The generated experimental data are shown for each model with corresponding exponential and power regression curves. The results of software modeling confirm the use of LSE approach. During the software implementation, the predicted values of the incoming call flow to the system were simulated.