A new least-squares approach to differintegration modeling

Signal Processing, Vol. 86, nº 10

Comments on ‘‘Modeling fractional stochastic systems as non-random fractional dynamics driven Brownian motions

Applied Mathematical Modelling, Vol.33

On the fractional central differences and derivatives

Fractional central differences and derivatives are studied in this article. These are generalisations to real orders of the ordinary positive (even and odd) integer order differences and derivatives, and also coincide with the well known Riesz potentials. The coherence of these definitions is studied by applying the definitions to functions with Fourier transformable functions. Some properties of these derivatives are presented and particular cases studied.

Fractional central differences and derivatives

Journal of Vibration and Control, Vol. 14, Nº 9-10

A coherent approach to non-integer order derivatives

Signal Processing, vol. 86, nº 10

Pseudo-fractional ARMA modelling using a double Levinson recursion

IET Control Theory & Applications, Vol. 1, Nº 1

A new symmetric fractional B-spline

Signal Processing, Vol. 83, nº 11

Fractional discrete-time signal processing: scale conversion and linear prediction

Nonlinear Dynamics, Vol. 29

A fractional linear system view of the fractional brownian motion

Nonlinear Dynamics, Vol. 38

Fractional central differences and derivatives

Journal of Vibration and Control, 14(9–10): 1255–1266, 2008

Transitional dynamics of an endogenous growth model with an erosion effect

The convergence features of an Endogenous Growth model with Physical capital, Human Capital and R&D have been studied. We add an erosion effect (supported by empirical evidence) to this model, and fully characterize its convergence properties. The dynamics is described by a fourth-order system of differential equations. We show that the model converges along a one-dimensional stable manifold and that its equilibrium is saddle-path stable. We also argue that one of the implications of considering this “erosion effect” is the increase in the adherence of the model to data.

Dynamics of serotonergic neurons revealed by fiber photometry

This work was developed in the context of the MIT Portugal Program, area of Bioengineering Systems, in collaboration with the Champalimaud Research Programme, Champalimaud Center for the Unknown, Lisbon, Portugal. The project entitled Dynamics of serotonergic neurons revealed by fiber photometry was carried out at Instituto Gulbenkian de Ciência, Oeiras, Portugal and at the Champalimaud Research Programme, Champalimaud Center for the Unknown, Lisbon, Portugal