Linear stochastic systems
Kalman filtering: with real-time applications (2nd ed.)
Kalman filtering: with real-time applications (2nd ed.)
Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Matrix inverse operation convolution: three models description
ISPRA'09 Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation
| Hi-index | 0.00 |
Using a multivariable dynamic model for describing startup times of real Time Tasks supposing the following considerations: The system is stationary, first order, with jitter and external perturbations bounded with a normal distribution without correlation that closely represent periodical behavior of real time tasks. To bear closer the task model in a concurrent system, systems internal dynamics are required, those are represented through the parameter matrix in function of output vectors in the regressive model as is for perturbations, but knowing their value is work for a multivariable estimator. Results of an example performed on a real-time platform are presented, considering periodic and concurrent tasks; an instrumental variable algorithm is used because of his good convergence time and his relatively easy implementation.