Left-Inverses of Fractional Laplacian and Sparse Stochastic Processes

The fractional Laplacian $(-\triangle)^{\gamma/2}$ commutes with the primary coordination transformations in the Euclidean space \RR^d: dilation, translation and rotation, and has tight link to splines, fractals and stable Levy processes. For $0<\gamma<d$, its inverse is the classical Riesz potential $I_\gamma$ which is dilation-invariant and translation-invariant. In this work, we investigate the functional properties (continuity, decay and invertibility) of an extended class of differential operators that share those invariance properties. In particular, we extend the definition of the classical Riesz potential $I_\gamma$ to any non-integer number $\gamma$ larger than $d$ and show that it is the unique left-inverse of the fractional Laplacian $(-\triangle)^{\gamma/2}$ which is dilation-invariant and translation-invariant. We observe that, for any $1\le p\le \infty$ and $\gamma\ge d(1-1/p)$, there exists a Schwartz function $f$ such that $I_\gamma f$ is not $p$-integrable. We then introduce the new unique left-inverse $I_{\gamma, p}$ of the fractional Laplacian $(-\triangle)^{\gamma/2}$ with the property that $I_{\gamma, p}$ is dilation-invariant (but not translation-invariant) and that $I_{\gamma, p}f$ is $p$-integrable for any Schwartz function $f$. We finally apply that linear operator $I_{\gamma, p}$ with $p=1$ to solve the stochastic partial differential equation $(-\triangle)^{\gamma/2} \Phi=w$ with white Poisson noise as its driving term $w$.Comment: Advances in Computational Mathematics, accepte

Sampling and Reconstruction of Signals in a Reproducing Kernel Subspace of Lp(Rd)L^p({\Bbb R}^d)

In this paper, we consider sampling and reconstruction of signals in a reproducing kernel subspace of L^p(\Rd), 1\le p\le \infty, associated with an idempotent integral operator whose kernel has certain off-diagonal decay and regularity. The space of $p$-integrable non-uniform splines and the shift-invariant spaces generated by finitely many localized functions are our model examples of such reproducing kernel subspaces of L^p(\Rd). We show that a signal in such reproducing kernel subspaces can be reconstructed in a stable way from its samples taken on a relatively-separated set with sufficiently small gap. We also study the exponential convergence, consistency, and the asymptotic pointwise error estimate of the iterative approximation-projection algorithm and the iterative frame algorithm for reconstructing a signal in those reproducing kernel spaces from its samples with sufficiently small gap

The abcabc-problem for Gabor systems

A Gabor system generated by a window function $\phi$ and a rectangular lattice $a \Z\times \Z/b$ is given by $${\mathcal G}(\phi, a \Z\times \Z/b):=\{e^{-2\pi i n t/b} \phi(t- m a):\ (m, n)\in \Z\times \Z\}.$$ One of fundamental problems in Gabor analysis is to identify window functions $\phi$ and time-frequency shift lattices $a \Z\times \Z/b$ such that the corresponding Gabor system ${\mathcal G}(\phi, a \Z\times \Z/b)$ is a Gabor frame for $L^2(\R)$, the space of all square-integrable functions on the real line $\R$. In this paper, we provide a full classification of triples $(a,b,c)$ for which the Gabor system ${\mathcal G}(\chi_I, a \Z\times \Z/b)$ generated by the ideal window function $\chi_I$ on an interval $I$ of length $c$ is a Gabor frame for $L^2(\R)$. For the classification of such triples $(a, b, c)$ (i.e., the $abc$-problem for Gabor systems), we introduce maximal invariant sets of some piecewise linear transformations and establish the equivalence between Gabor frame property and triviality of maximal invariant sets. We then study dynamic system associated with the piecewise linear transformations and explore various properties of their maximal invariant sets. By performing holes-removal surgery for maximal invariant sets to shrink and augmentation operation for a line with marks to expand, we finally parameterize those triples $(a, b, c)$ for which maximal invariant sets are trivial. The novel techniques involving non-ergodicity of dynamical systems associated with some novel non-contractive and non-measure-preserving transformations lead to our arduous answer to the $abc$-problem for Gabor systems

Spectral measures with arbitrary Hausdorff dimensions

In this paper, we consider spectral properties of Riesz product measures supported on homogeneous Cantor sets and we show the existence of spectral measures with arbitrary Hausdorff dimensions, including non-atomic zero-dimensional spectral measures and one-dimensional singular spectral measures

Recovery of bilevel causal signals with finite rate of innovation using positive sampling kernels

Bilevel signal $x$ with maximal local rate of innovation $R$ is a continuous-time signal that takes only two values 0 and 1 and that there is at most one transition position in any time period of 1/R.In this note, we introduce a recovery method for bilevel causal signals $x$ with maximal local rate of innovation $R$ from their uniform samples $x*h(nT), n\ge 1$, where the sampling kernel $h$ is causal and positive on $(0, T)$, and the sampling rate $\tau:=1/T$ is at (or above) the maximal local rate of innovation $R$. We also discuss stability of the bilevel signal recovery procedure in the presence of bounded noises

Reconstruction of sparse wavelet signals from partial Fourier measurements

In this paper, we show that high-dimensional sparse wavelet signals of finite levels can be constructed from their partial Fourier measurements on a deterministic sampling set with cardinality about a multiple of signal sparsity