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The method is validated by comparison with regression of the analytical solution of a linear vibration.
Then we develop an algorithm to compute a solution of a linear variational relation problem.
The Wright function plays an important role in the solution of a linear partial differential equation.
This involves a solution of a linear system with the complex symmetric matrix Q.
The optimal translations are then recovered directly through the solution of a linear equation system.
The predictor is designed using Lyapunov-based methods, by numerical solution of a linear matrix inequality.
This method, at each time step, requires the solution of a linear, symmetric, 5-diagonal system.
The system description is the solution of a linear partial differential equation (PDE).
The proposed method is computationally simple since it requires the solution of a linear system of equations.
Then we give a design method of the observer that is dependent on the solution of a linear matrix inequality.
Weights are either based on the known measurement noise or given by the solution of a linear matrix inequality problem.
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