2,572 research outputs found
A multiscale collocation method for fractional differential problems
We introduce a multiscale collocation method to numerically solve differential problems involving both ordinary and fractional
derivatives of high order. The proposed method uses multiresolution analyses (MRA) as approximating spaces and takes advantage
of a finite difference formula that allows us to express both ordinary and fractional derivatives of the approximating function in a closed form. Thus, the method is easy to implement, accurate and efficient. The convergence and the stability of the multiscale
collocation method are proved and some numerical results are shown.We introduce a multiscale collocation method to numerically solve differential problems involving both ordinary and fractional
derivatives of high order. The proposed method uses multiresolution analyses (MRA) as approximating spaces and takes advantage
of a finite difference formula that allows us to express both ordinary and fractional derivatives of the approximating function in a closed form. Thus, the method is easy to implement, accurate and efficient. The convergence and the stability of the multiscale
collocation method are proved and some numerical results are shown
Fractional Operators, Dirichlet Averages, and Splines
Fractional differential and integral operators, Dirichlet averages, and
splines of complex order are three seemingly distinct mathematical subject
areas addressing different questions and employing different methodologies. It
is the purpose of this paper to show that there are deep and interesting
relationships between these three areas. First a brief introduction to
fractional differential and integral operators defined on Lizorkin spaces is
presented and some of their main properties exhibited. This particular approach
has the advantage that several definitions of fractional derivatives and
integrals coincide. We then introduce Dirichlet averages and extend their
definition to an infinite-dimensional setting that is needed to exhibit the
relationships to splines of complex order. Finally, we focus on splines of
complex order and, in particular, on cardinal B-splines of complex order. The
fundamental connections to fractional derivatives and integrals as well as
Dirichlet averages are presented
Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems
This paper deals with the resolution of inverse problems in a periodic
setting or, in other terms, the reconstruction of periodic continuous-domain
signals from their noisy measurements. We focus on two reconstruction
paradigms: variational and statistical. In the variational approach, the
reconstructed signal is solution to an optimization problem that establishes a
tradeoff between fidelity to the data and smoothness conditions via a quadratic
regularization associated to a linear operator. In the statistical approach,
the signal is modeled as a stationary random process defined from a Gaussian
white noise and a whitening operator; one then looks for the optimal estimator
in the mean-square sense. We give a generic form of the reconstructed signals
for both approaches, allowing for a rigorous comparison of the two.We fully
characterize the conditions under which the two formulations yield the same
solution, which is a periodic spline in the case of sampling measurements. We
also show that this equivalence between the two approaches remains valid on
simulations for a broad class of problems. This extends the practical range of
applicability of the variational method
Exponential Splines of Complex Order
We extend the concept of exponential B-spline to complex orders. This
extension contains as special cases the class of exponential splines and also
the class of polynomial B-splines of complex order. We derive a time domain
representation of a complex exponential B-spline depending on a single
parameter and establish a connection to fractional differential operators
defined on Lizorkin spaces. Moreover, we prove that complex exponential splines
give rise to multiresolution analyses of and define wavelet
bases for
Construction of Hilbert Transform Pairs of Wavelet Bases and Gabor-like Transforms
We propose a novel method for constructing Hilbert transform (HT) pairs of
wavelet bases based on a fundamental approximation-theoretic characterization
of scaling functions--the B-spline factorization theorem. In particular,
starting from well-localized scaling functions, we construct HT pairs of
biorthogonal wavelet bases of L^2(R) by relating the corresponding wavelet
filters via a discrete form of the continuous HT filter. As a concrete
application of this methodology, we identify HT pairs of spline wavelets of a
specific flavor, which are then combined to realize a family of complex
wavelets that resemble the optimally-localized Gabor function for sufficiently
large orders.
Analytic wavelets, derived from the complexification of HT wavelet pairs,
exhibit a one-sided spectrum. Based on the tensor-product of such analytic
wavelets, and, in effect, by appropriately combining four separable
biorthogonal wavelet bases of L^2(R^2), we then discuss a methodology for
constructing 2D directional-selective complex wavelets. In particular,
analogous to the HT correspondence between the components of the 1D
counterpart, we relate the real and imaginary components of these complex
wavelets using a multi-dimensional extension of the HT--the directional HT.
Next, we construct a family of complex spline wavelets that resemble the
directional Gabor functions proposed by Daugman. Finally, we present an
efficient FFT-based filterbank algorithm for implementing the associated
complex wavelet transform.Comment: 36 pages, 8 figure
A fractional B-spline collocation method for the numerical solution of fractional predator-prey models
We present a collocation method based on fractional B-splines for the solution of fractional differential problems. The key-idea is to use the space generated by the fractional B-splines, i.e., piecewise polynomials of noninteger degree, as approximating space. Then, in the collocation step the fractional derivative of the approximating function is approximated accurately and efficiently by an exact differentiation rule that involves the generalized finite difference operator. To show the effectiveness of the method for the solution of nonlinear dynamical systems of fractional order, we solved the fractional Lotka-Volterra model and a fractional predator-pray model with variable coefficients. The numerical tests show that the method we proposed is accurate while keeping a low computational cost
A fractional wavelet Galerkin method for the fractional diffusion problem
The aim of this paper is to solve some fractional differential problems hav-
ing time fractional derivative by means of a wavelet Galerkin method that
uses the fractional scaling functions introduced in a previpous paper as approximating
functions. These refinable functions, which are a generalization of the
fractional B-splines, have many interesting approximation properties.
In particular, their fractional derivatives have a closed form that involves
just the fractional difference operator. This allows us to construct accurate
and efficient numerical methods to solve fractional differential problems.
Some numerical tests on a fractional diffusion problem will be given
- …