666 research outputs found

    A Note on BIBO Stability

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    The statements on the BIBO stability of continuous-time convolution systems found in engineering textbooks are often either too vague (because of lack of hypotheses) or mathematically incorrect. What is more troubling is that they usually exclude the identity operator. The purpose of this note is to clarify the issue while presenting some fixes. In particular, we show that a linear shift-invariant system is BIBO-stable in the L∞L_\infty-sense if and only if its impulse response is included in the space of bounded Radon measures, which is a superset of L1(R)L_1(\mathbb{R}) (Lebesgue's space of absolutely integrable functions). As we restrict the scope of this characterization to the convolution operators whose impulse response is a measurable function, we recover the classical statement

    Autofocus for digital Fresnel holograms by use of a Fresnelet-sparsity criterion

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    We propose a robust autofocus method for reconstructing digital Fresnel holograms. The numerical reconstruction involves simulating the propagation of a complex wave front to the appropriate distance. Since the latter value is difficult to determine manually, it is desirable to rely on an automatic procedure for finding the optimal distance to achieve high-quality reconstructions. Our algorithm maximizes a sharpness metric related to the sparsity of the signal’s expansion in distance-dependent waveletlike Fresnelet bases. We show results from simulations and experimental situations that confirm its applicability

    Left-Inverses of Fractional Laplacian and Sparse Stochastic Processes

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    The fractional Laplacian (−△)γ/2(-\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<γ<d0<\gamma<d, its inverse is the classical Riesz potential IγI_\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 IγI_\gamma to any non-integer number γ\gamma larger than dd and show that it is the unique left-inverse of the fractional Laplacian (−△)γ/2(-\triangle)^{\gamma/2} which is dilation-invariant and translation-invariant. We observe that, for any 1≤p≤∞1\le p\le \infty and γ≥d(1−1/p)\gamma\ge d(1-1/p), there exists a Schwartz function ff such that IγfI_\gamma f is not pp-integrable. We then introduce the new unique left-inverse Iγ,pI_{\gamma, p} of the fractional Laplacian (−△)γ/2(-\triangle)^{\gamma/2} with the property that Iγ,pI_{\gamma, p} is dilation-invariant (but not translation-invariant) and that Iγ,pfI_{\gamma, p}f is pp-integrable for any Schwartz function ff. We finally apply that linear operator Iγ,pI_{\gamma, p} with p=1p=1 to solve the stochastic partial differential equation (−△)γ/2Φ=w(-\triangle)^{\gamma/2} \Phi=w with white Poisson noise as its driving term ww.Comment: Advances in Computational Mathematics, accepte

    On the Hilbert transform of wavelets

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    A wavelet is a localized function having a prescribed number of vanishing moments. In this correspondence, we provide precise arguments as to why the Hilbert transform of a wavelet is again a wavelet. In particular, we provide sharp estimates of the localization, vanishing moments, and smoothness of the transformed wavelet. We work in the general setting of non-compactly supported wavelets. Our main result is that, in the presence of some minimal smoothness and decay, the Hilbert transform of a wavelet is again as smooth and oscillating as the original wavelet, whereas its localization is controlled by the number of vanishing moments of the original wavelet. We motivate our results using concrete examples.Comment: Appears in IEEE Transactions on Signal Processing, vol. 59, no. 4, pp. 1890-1894, 201

    Construction of Hilbert Transform Pairs of Wavelet Bases and Gabor-like Transforms

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    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
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