Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
A GEOMETRIC APPROACH TO THE CASCADE APPROXIMATION OPERATOR FOR WAVELETS1 Palle E. T. Jorgensen This paper is devoted to an approximation problem for operators in Hilbert space, that appears when one tries to study geometrically the cascade algorithm in wavelet theory. Let H be a Hilbert space, and let π be a representation of L ∞ (T) on H. Let R be a positive operator in L ∞ (T) such that R (11) = 1 1, where 1 1 denotes the constant function 1. We study operators M on H (bounded, but noncontractive) such thatwhere the * refers to Hilbert space adjoint. We give a complete orthogonal expansion of H which reduces π such that M acts as a shift on one part, and the residual part is H (∞) = n [M n H], where [M n H] is the closure of the range of M n . The shift part is present, we show, if and only if ker (M * ) = {0}. We apply the operator-theoretic results to the refinement operator (or cascade algorithm) from wavelet theory. Using the representation π, we show that, for this wavelet operator M, the components in the decomposition are unitarily, and canonically, equivalent to spaces L 2 (E n ) ⊂ L 2 (R), where E n ⊂ R, n = 0, 1, 2, . . . , ∞, are measurable subsets which form a tiling of R; i.e., the union is R up to zero measure, and pairwise intersections of different E n 's have measure zero. We prove two results on the convergence of the cascade algorithm, and identify singular vectors for the starting point of the algorithm. Contents:1 In wavelet theory, one is given a subband filter, i.e., a function m 0 on the unit circle, satisfying (i)-(iii) from below and one wants to construct a scaling function ϕ (relative to m 0 ), i.e., a nonzero function ϕ on R satisfying the scaling relation ϕ = Mϕ (relation (1.1) in the paper). Here M = M m 0 is the so-called cascade operator defined bywhere a n are Fourier coefficients of the function m 0 . The scaling function ϕ is important because its shifts generate (under some analytic conditions) the so-called multiresolution subspace V = V (ϕ), which is used to construct the wavelets. There are several ways of constructing a scaling function ϕ. The cascade algorithm is one of the possibilities. In this algorithm one picks some simple function h and considers its iterations M n h. Clearly, if the iterations M n h converge to a nonzero function ϕ, the function ϕ satisfies ϕ = Mϕ, so the algorithm gives us a scaling function. We study the problem of convergence of this algorithm in the setting of an abstract Hilbert space. The cascade operator M has some very special structure. The Ruelle operator R, which appears naturally in this type of problem, gives us a way to describe this structure. Namely, the operator M is what we shall call a sub-isometry; see Definition 6.1. In fact the concept depends on a pair (R, π) where R is a Ruelle operator and π is a representation. It turns out that sub-isometries admit an analogue of the Kolmogorov-Wold decomposition for usual isometries. Using this decomposition, we obtain results about convergence of the cascade algorithm in an abstract ...
A GEOMETRIC APPROACH TO THE CASCADE APPROXIMATION OPERATOR FOR WAVELETS1 Palle E. T. Jorgensen This paper is devoted to an approximation problem for operators in Hilbert space, that appears when one tries to study geometrically the cascade algorithm in wavelet theory. Let H be a Hilbert space, and let π be a representation of L ∞ (T) on H. Let R be a positive operator in L ∞ (T) such that R (11) = 1 1, where 1 1 denotes the constant function 1. We study operators M on H (bounded, but noncontractive) such thatwhere the * refers to Hilbert space adjoint. We give a complete orthogonal expansion of H which reduces π such that M acts as a shift on one part, and the residual part is H (∞) = n [M n H], where [M n H] is the closure of the range of M n . The shift part is present, we show, if and only if ker (M * ) = {0}. We apply the operator-theoretic results to the refinement operator (or cascade algorithm) from wavelet theory. Using the representation π, we show that, for this wavelet operator M, the components in the decomposition are unitarily, and canonically, equivalent to spaces L 2 (E n ) ⊂ L 2 (R), where E n ⊂ R, n = 0, 1, 2, . . . , ∞, are measurable subsets which form a tiling of R; i.e., the union is R up to zero measure, and pairwise intersections of different E n 's have measure zero. We prove two results on the convergence of the cascade algorithm, and identify singular vectors for the starting point of the algorithm. Contents:1 In wavelet theory, one is given a subband filter, i.e., a function m 0 on the unit circle, satisfying (i)-(iii) from below and one wants to construct a scaling function ϕ (relative to m 0 ), i.e., a nonzero function ϕ on R satisfying the scaling relation ϕ = Mϕ (relation (1.1) in the paper). Here M = M m 0 is the so-called cascade operator defined bywhere a n are Fourier coefficients of the function m 0 . The scaling function ϕ is important because its shifts generate (under some analytic conditions) the so-called multiresolution subspace V = V (ϕ), which is used to construct the wavelets. There are several ways of constructing a scaling function ϕ. The cascade algorithm is one of the possibilities. In this algorithm one picks some simple function h and considers its iterations M n h. Clearly, if the iterations M n h converge to a nonzero function ϕ, the function ϕ satisfies ϕ = Mϕ, so the algorithm gives us a scaling function. We study the problem of convergence of this algorithm in the setting of an abstract Hilbert space. The cascade operator M has some very special structure. The Ruelle operator R, which appears naturally in this type of problem, gives us a way to describe this structure. Namely, the operator M is what we shall call a sub-isometry; see Definition 6.1. In fact the concept depends on a pair (R, π) where R is a Ruelle operator and π is a representation. It turns out that sub-isometries admit an analogue of the Kolmogorov-Wold decomposition for usual isometries. Using this decomposition, we obtain results about convergence of the cascade algorithm in an abstract ...
Abstract. In this paper we show how wavelets originating from multiresolution analysis of scale N give rise to certain representations of the Cuntz algebras O N , and conversely how the wavelets can be recovered from these representations. The representations are given on the Hilbert space L 2 (T) by (S i ξ) (z) = m i (z) ξ z N . We characterize the Wold decomposition of such operators. If the operators come from wavelets they are shifts, and this can be used to realize the representation on a certain Hardy space over L 2 (T). This is used to compare the usual scale-2 theory of wavelets with the scale-N theory. Also some other representations of O N of the above form called diagonal representations are characterized and classified up to unitary equivalence by a homological invariant.
Abstract. Let N ∈ N, N ≥ 2, be given. Motivated by wavelet analysis, we consider a class of normal representations of the C * -algebra A N on two unitary generators U , V subject to the relationThe representations are in one-to-one correspondence with solutions h ∈ L 1 (T), In multiresolution wavelet theory, there is a fundamental interplay and interconnection between the following two operators: M and R, where M is the cascade refinement operator and R is the corresponding transfer operator. We also denote the second of these, R, the Ruelle operator, because of its close connection to an operator that David Ruelle used first in his study of phase transitions in quantum statistical mechanics lattice models; see [Rue68], [May80],and [Rue78a]. We first recall the two operators here in a simple wavelet context, but the scope will be 1991 Mathematics Subject Classification. Primary 46L60, 47D25, 42A16, 43A65; Secondary 46L45, 42A65, 41A15.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.