Fractional order differentiation by integration: an application to fractional linear systems

Using the multiple stochastic integrals we prove an existence and uniqueness result for a linear stochastic equation driven by the fractional Brownian motion with any Hurst

Section 2 presents the basic properties of the linear fractional stable motion, the review of the probabilistic results from [5] and a multivariate limit theorem, which plays a key

In this paper, sufficient conditions for the robust stabilization of linear and non-linear fractional- order systems with non-linear uncertainty parameters with fractional

Recently, Sousa e Oliveira, through the ψ-Hilfer fractional operator, has ob- tained interesting and important results of the existence, uniqueness, stability and attractivity

The proposed identi?cation method is based on the recursive least squares algorithm applied to an ARX structure derived from the linear fractional order differential equation

The proposed identification method is based on the recursive least squares algorithm applied to a linear regression equation derived from the linear fractional order

In this context, the fundamental functions are defined as the functions which will be used in the solution of the state-space linear fractional order systems

The proposed identification technique is based on the recursive least squares algorithm applied to a linear regression equation using adjustable fractional order differentiator