7,436 research outputs found
Model Reduction of Multi-Dimensional and Uncertain Systems
We present model reduction methods with guaranteed error bounds for systems represented by a Linear Fractional Transformation (LFT) on a repeated scalar uncertainty structure. These reduction methods can be interpreted either as doing state order reduction for multi-dimensionalsystems, or as uncertainty simplification in the case of uncertain systems, and are based on finding solutions to a pair of Linear Matrix Inequalities (LMIs). A related necessary and sufficient condition for the exact reducibility of stable uncertain systems is also presented
Diffusive representations for fractional Laplacian: systems theory framework and numerical issues
Bridging the gap between an abstract definition of pseudo-differential operators, such as (-\Delta)^{\gamma} for - 1/2 < \gamma < 1/2, and a concrete way to represent them has proved difficult; deriving stable numerical schemes for such operators is not an easy task either. Thus, the framework of diffusive representations, as already developed for causal fractional integrals and derivatives,
is being applied to fractional Laplacian: it can be seen as an extension of the Wiener-ÂHopf factorization and splitting techniques to irrational transfer functions
Functional characterization of generalized Langevin equations
We present an exact functional formalism to deal with linear Langevin
equations with arbitrary memory kernels and driven by any noise structure
characterized through its characteristic functional. No others hypothesis are
assumed over the noise, neither the fluctuation dissipation theorem. We found
that the characteristic functional of the linear process can be expressed in
terms of noise's functional and the Green function of the deterministic
(memory-like) dissipative dynamics. This object allow us to get a procedure to
calculate all the Kolmogorov hierarchy of the non-Markov process. As examples
we have characterized through the 1-time probability a noise-induced interplay
between the dissipative dynamics and the structure of different noises.
Conditions that lead to non-Gaussian statistics and distributions with long
tails are analyzed. The introduction of arbitrary fluctuations in fractional
Langevin equations have also been pointed out
The exit-time problem for a Markov jump process
The purpose of this paper is to consider the exit-time problem for a
finite-range Markov jump process, i.e, the distance the particle can jump is
bounded independent of its location. Such jump diffusions are expedient models
for anomalous transport exhibiting super-diffusion or nonstandard normal
diffusion. We refer to the associated deterministic equation as a
volume-constrained nonlocal diffusion equation. The volume constraint is the
nonlocal analogue of a boundary condition necessary to demonstrate that the
nonlocal diffusion equation is well-posed and is consistent with the jump
process. A critical aspect of the analysis is a variational formulation and a
recently developed nonlocal vector calculus. This calculus allows us to pose
nonlocal backward and forward Kolmogorov equations, the former equation
granting the various moments of the exit-time distribution.Comment: 15 pages, 7 figure
Wavelet versus Detrended Fluctuation Analysis of multifractal structures
We perform a comparative study of applicability of the Multifractal Detrended
Fluctuation Analysis (MFDFA) and the Wavelet Transform Modulus Maxima (WTMM)
method in proper detecting of mono- and multifractal character of data. We
quantify the performance of both methods by using different sorts of artificial
signals generated according to a few well-known exactly soluble mathematical
models: monofractal fractional Brownian motion, bifractal Levy flights, and
different sorts of multifractal binomial cascades. Our results show that in
majority of situations in which one does not know a priori the fractal
properties of a process, choosing MFDFA should be recommended. In particular,
WTMM gives biased outcomes for the fractional Brownian motion with different
values of Hurst exponent, indicating spurious multifractality. In some cases
WTMM can also give different results if one applies different wavelets. We do
not exclude using WTMM in real data analysis, but it occurs that while one may
apply MFDFA in a more automatic fashion, WTMM has to be applied with care. In
the second part of our work, we perform an analogous analysis on empirical data
coming from the American and from the German stock market. For this data both
methods detect rich multifractality in terms of broad f(alpha), but MFDFA
suggests that this multifractality is poorer than in the case of WTMM.Comment: substantially extended version, to appear in Phys.Rev.
Systems control theory applied to natural and synthetic musical sounds
Systems control theory is a far developped field which helps to study stability, estimation and control of dynamical systems. The physical behaviour of musical instruments, once described by dynamical systems, can then be controlled and numerically simulated for many purposes.
The aim of this paper is twofold: first, to provide the theoretical background on linear system theory, both in continuous and discrete time, mainly in the case of a finite number of degrees of freedom ; second, to give illustrative examples on wind instruments, such as the vocal tract represented as a waveguide, and a sliding flute
Paradoxical diffusion: Discriminating between normal and anomalous random walks
Commonly, normal diffusive behavior is characterized by a linear dependence
of the second central moment on time, , while anomalous
behavior is expected to show a different time dependence, with for
superdiffusive motions. Here we demonstrate that this kind of qualification, if
applied straightforwardly, may be misleading: There are anomalous transport
motions revealing perfectly "normal" diffusive character (), yet being non-Markov and non-Gaussian in nature. We use recently developed
framework \cite[Phys. Rev. E \textbf{75}, 056702 (2007)]{magdziarz2007b} of
Monte Carlo simulations which incorporates anomalous diffusion statistics in
time and space and creates trajectories of such an extended random walk. For
special choice of stability indices describing statistics of waiting times and
jump lengths, the ensemble analysis of paradoxical diffusion is shown to hide
temporal memory effects which can be properly detected only by examination of
formal criteria of Markovianity (fulfillment of the Chapman-Kolmogorov
equation).Comment: 8 pages, 7 figure
Topological properties and fractal analysis of recurrence network constructed from fractional Brownian motions
Many studies have shown that we can gain additional information on time
series by investigating their accompanying complex networks. In this work, we
investigate the fundamental topological and fractal properties of recurrence
networks constructed from fractional Brownian motions (FBMs). First, our
results indicate that the constructed recurrence networks have exponential
degree distributions; the relationship between and of recurrence networks decreases with the Hurst
index of the associated FBMs, and their dependence approximately satisfies
the linear formula . Moreover, our numerical results of
multifractal analysis show that the multifractality exists in these recurrence
networks, and the multifractality of these networks becomes stronger at first
and then weaker when the Hurst index of the associated time series becomes
larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst
index possess the strongest multifractality. In addition, the
dependence relationships of the average information dimension on the Hurst index can also be
fitted well with linear functions. Our results strongly suggest that the
recurrence network inherits the basic characteristic and the fractal nature of
the associated FBM series.Comment: 25 pages, 1 table, 15 figures. accepted by Phys. Rev.
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