Ortigueira, MD, Coito FJ.
2010.
System initial conditions vs derivative initial conditions. Computers & Mathematics with Applications. : Elsevier Ltd
AbstractThe alternative system initial conditions versus the derivative initial conditions is focused in this paper. It is shown that Riemann?Liouville and Caputo initial conditions result from the corresponding derivative and not necessarily from the system at hand. To setup the correct system initialization, a formulation generalizing the integer order approach is presented. This is based on a generalization to the fractional environment of the well known jump formula. The obtained scheme is very general and does not depend on any transform. Besides, it can also be used in the time variant case. The Riemann?Liouville and Caputo initial conditions are interpreted in terms of this general framework and deduced equations where they are correct.
Ktonas, PY, Golemati S, Xanthopoulos P, Sakkalis V, Ortigueira MD, Tsekou H, Zervakis M, Paparrigopoulos T, Bonakis A, Economou NT.
2009.
Time?frequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: Possibility for dementia biomarkers? Journal of Neuroscience Methods. 185:133–142., Number 1
AbstractThe time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies and can be quantified with a number of techniques. In this paper, real and simulated sleep spindles were regarded as AM?FM signals modeled by six parameters that define the instantaneous envelope (IE) and instantaneous frequency (IF) waveforms for a sleep spindle. These parameters were estimated using four different methods, namely the Hilbert transform (HT), complex demodulation (CD), matching pursuit (MP) and wavelet transform (WT). The average error in estimating these parameters was lowest for HT, higher but still less than 10% for CD and MP, and highest (greater than 10%) for WT. The signal distortion induced by the use of a given method was greatest in the case of HT and MP. These two techniques would necessitate the removal of about 0.4 s from the spindle data, which is an important limitation for the case of spindles with duration less than 1 s. Although the CD method may lead to a higher error than HT and MP, it requires a removal of only about 0.23 s of data. An application of this sleep spindle parameterization via the CD method is proposed, in search of efficient EEG-based biomarkers in dementia. Preliminary results indicate that the proposed parameterization may be promising, since it can quantify specific differences in IE and IF characteristics between sleep spindles from dementia subjects and those from aged controls.
Ortigueira, M, Tenreiro-Machado JA, da Costa JSá.
2005.
Which Differintegration?, July IEE Proceedings Vision, Image & Signal Processing. 152:846–850., Number 6: IET
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