Frame Functions and Completeness of Inner Product Spaces Annales De L’I
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L2-Theory of Semiclassical Psdos: Hilbert-Schmidt And
2 LECTURE 13: L -THEORY OF SEMICLASSICAL PSDOS: HILBERT-SCHMIDT AND TRACE CLASS OPERATORS In today's lecture we start with some abstract properties of Hilbert-Schmidt operators and trace class operators. Then we will investigate the following natural t questions: for which class of symbols, the quantized operator Op~(a) is a Hilbert- Schmidt or trace class operator? How to compute its trace? 1. Hilbert-Schmidt and Trace class operators: Abstract theory { Definitions via singular values. As we have mentioned last time, we are aiming at developing the spectral theory for semiclassical pseudodifferential operators. For a 2 S(m), where m is a decaying t 2 n symbol, we showed that Op~(a) is a compact operator acting on L (R ). As a t consequence, either Op~(a) has only finitely many nonzero eigenvalues, or it has infinitely nonzero eigenvalues which can be arranged to a sequence whose norms converges to 0. However, in general the eigenvalues of a compact operator A are non-real. A very simple way to get real eigenvalues is to consider the operator A∗A, which is 1 a compact self-adjoint linear operator acting on L2(Rn). Thus the eigenvalues of A∗A can be list2 in decreasing order as 2 2 2 s1 ≥ s2 ≥ s3 ≥ · · · : The numbers sj (which will always be taken to be the positive one) are called the singular values of A. Definition 1.1. We say a compact operator3 A is a Hilbert-Schmidt operator if !1=2 X 2 (1) kAkHS := sj < +1: j The number kAkHS is called the Hilbert-Schmidt norm (or Schatten 2-norm) of A. -
Sums of Hilbert Space Frames 1
SUMS OF HILBERT SPACE FRAMES SOFIAN OBEIDAT, SALTI SAMARAH, PETER G. CASAZZA AND JANET C. TREMAIN Abstract. We give simple necessary and sufficient conditions on Bessel sequences {fi} and {gi} and operators L1,L2 on a Hilbert space H so that {L1fi + L2gi} is a frame for H. This allows us to construct a large number of new Hilbert space frames from existing frames. 1. Introduction Frames for Hilbert spaces were introduced by Duffin and Schaeffer [8] as a part of their research in non-harmonic Fourier series. Their work on frames was somewhat forgotten until 1986 when Daubechies, Grossmann and Meyer [13] brought it all back to life during their fundamental work on wavelets. Today, frame theory plays an important role not just in signal processing, but also in dozens of applied areas (See [1, 2]). Holub [12] showed that if {xn} is any normalized basis for a Hilbert space H and {fn} is the associated dual basis of coefficient functionals, then the sequence {xn + fn} is again a basis for H. In this paper we study cases in which new frames can be obtained from old ones. Throughout H denotes a separable Hilbert space and HN is the Nth dimensional Hilbert space. A frame for H is a family of vectors fi ∈ H, for i ∈ I for which there exist constants A, B > 0 satisfying: 2 X 2 2 (1.1) Akfk ≤ |hf, fii| ≤ Bkfk i∈I for all f ∈ H. A and B are called the lower and upper frame bounds respectively. If A = B, this is called an A-tight frame. -
Designing Structured Tight Frames Via an Alternating Projection Method Joel A
1 Designing Structured Tight Frames via an Alternating Projection Method Joel A. Tropp, Student Member, IEEE, Inderjit S. Dhillon, Member, IEEE, Robert W. Heath Jr., Member, IEEE and Thomas Strohmer Abstract— Tight frames, also known as general Welch-Bound- tight frame to a given ensemble of structured vectors; then Equality sequences, generalize orthonormal systems. Numer- it finds the ensemble of structured vectors nearest to the ous applications—including communications, coding and sparse tight frame; and it repeats the process ad infinitum. This approximation—require finite-dimensional tight frames that pos- sess additional structural properties. This paper proposes a technique is analogous to the method of projection on convex versatile alternating projection method that is flexible enough to sets (POCS) [4], [5], except that the class of tight frames is solve a huge class of inverse eigenvalue problems, which includes non-convex, which complicates the analysis significantly. Nev- the frame design problem. To apply this method, one only needs ertheless, our alternating projection algorithm affords simple to solve a matrix nearness problem that arises naturally from implementations, and it provides a quick route to solve difficult the design specifications. Therefore, it is fast and easy to develop versions of the algorithm that target new design problems. frame design problems. This article offers extensive numerical Alternating projection is likely to succeed even when algebraic evidence that our method succeeds for several important cases. constructions are unavailable. We argue that similar techniques apply to a huge class of To demonstrate that alternating projection is an effective tool inverse eigenvalue problems. for frame design, the article studies some important structural There is a major conceptual difference between the use properties in detail. -
FRAME WAVELET SETS in R §1. Introduction a Collection of Elements
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 129, Number 7, Pages 2045{2055 S 0002-9939(00)05873-1 Article electronically published on December 28, 2000 FRAME WAVELET SETS IN R X. DAI, Y. DIAO, AND Q. GU (Communicated by David R. Larson) Abstract. In this paper, we try to answer an open question raised by Han and Larson, which asks about the characterization of frame wavelet sets. We completely characterize tight frame wavelet sets. We also obtain some nec- essary conditions and some sufficient conditions for a set E to be a (general) frame wavelet set. Some results are extended to frame wavelet functions that are not defined by frame wavelet set. Several examples are presented and compared with some known results in the literature. x1. Introduction A collection of elements fxj : j 2Jgin a Hilbert space H is called a frame if there exist constants A and B,0<A≤ B<1, such that X 2 2 2 (1) Akfk ≤ jhf;xj ij ≤ Bkfk j2J for all f 2H. The supremum of all such numbers A and the infimum of all such numbers B are called the frame bounds of the frame and denoted by A0 and B0 respectively. The frame is called a tight frame when A0 = B0 andiscalleda normalized tight frame when A0 = B0 = 1. Any orthonormal basis in a Hilbert space is a normalized tight frame. The concept of frame first appeared in the late 40's and early 50's (see [6], [13] and [12]). The development and study of wavelet theory during the last decade also brought new ideas and attention to frames because of their close connections. -
The Contourlet Transform: an Efficient Directional Multiresolution Image Representation Minh N
IEEE TRANSACTIONS ON IMAGE PROCESSING 1 The Contourlet Transform: An Efficient Directional Multiresolution Image Representation Minh N. Do, Member, IEEE, and Martin Vetterli, Fellow, IEEE Abstract— The limitations of commonly used separable ex- representation has to be obtained by structured transforms and tensions of one-dimensional transforms, such as the Fourier fast algorithms. and wavelet transforms, in capturing the geometry of image For one-dimensional piecewise smooth signals, like scan- edges are well known. In this paper, we pursue a “true” two- dimensional transform that can capture the intrinsic geometrical lines of an image, wavelets have been established as the right structure that is key in visual information. The main challenge tool, because they provide an optimal representation for these in exploring geometry in images comes from the discrete nature signals in a certain sense [1], [2]. In addition, the wavelet of the data. Thus, unlike other approaches, such as curvelets, representation is amenable to efficient algorithms; in particular that first develop a transform in the continuous domain and it leads to fast transforms and convenient tree data structures. then discretize for sampled data, our approach starts with a discrete-domain construction and then studies its convergence These are the key reasons for the success of wavelets in to an expansion in the continuous domain. Specifically, we many signal processing and communication applications; for construct a discrete-domain multiresolution and multidirection example, the wavelet transform was adopted as the transform expansion using non-separable filter banks, in much the same way for the new image-compression standard, JPEG-2000 [3]. -
The Canonical Dual Frame of a Wavelet Frame
Applied and Computational Harmonic Analysis 12, 269–285 (2002) doi:10.1006/acha.2002.0381 The Canonical Dual Frame of a Wavelet Frame Ingrid Daubechies 1 PACM, Department of Mathematics, Princeton University, Fine Hall, Washington Road, Princeton, New Jersey 08544 E-mail: [email protected] and Bin Han 2 Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta T6G 2G1, Canada E-mail: [email protected] Communicated by Charles K. Chui Received July 11, 2000; revised December 20, 2001 In this paper we show that there exist wavelet frames that have nice dual wavelet frames, but for which the canonical dual frame does not consist of wavelets, i.e., cannot be generated by the translates and dilates of a single function. 2002 Elsevier Science (USA) Key Words: wavelet frame; the canonical dual frame; dual wavelet frame. 1. INTRODUCTION We start by recalling some notations and definitions. Let H be a Hilbert space. A set of elements {hk}k∈Z in H is said to be a frame (see [5]) in H if there exist two positive constants A and B such that 2 2 2 Af ≤ |f,hk| ≤ Bf , ∀f ∈ H, (1.1) k∈Z where A and B are called the lower frame bound and upper frame bound, respectively. In particular, when A = B = 1, we say that {hk}k∈Z is a (normalized) tight frame in H.The 1 Research was partially supported by NSF Grants DMS-9872890, DMS-9706753 and AFOSR Grant F49620- 98-1-0044. Web: http://www.princeton.edu/~icd. 2 Research was supported by NSERC Canada under Grant G121210654 and by Alberta Innovation and Science REE under Grant G227120136. -
Quantization in Signal Processing with Frame Theory
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Vanderbilt Electronic Thesis and Dissertation Archive QUANTIZATION IN SIGNAL PROCESSING WITH FRAME THEORY By JIAYI JIANG Dissertation Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in Mathematics May, 2016 Nashville, Tennessee Approved: Alexander Powell Akram Aldroubi Doug Hardin Brett Byram ©Copyright by Jiayi Jiang, 2016. All Rights Reserved ii ACKNOWLEDGEMENTS Firstly, I would like to express my sincere gratitude to my advisor, Alexander.M.Powell. He taught me too many thing in these five years which are not only on mathematics research but also on how to be a polite and organised person. Thanks a lot for his encouragement, patience and professional advices. I really appreciate for his supporting and helping when I decide to work in industry instead of academic. All of these mean a lot to me! My time in Vanderbilt has been a lot of fun. Thanks for the faculty of the math depart- ment. Thanks for all my teachers, Akram Aldroubi, Doug Hardin, Mark Ellingham, Mike Mihalik, Edward Saff. Each Professors in these list taught me at least one course which I will be benefited from them in my future carer. I really enjoy the different way of teaching from these professors. Thanks for my Vandy friends, Corey Jones, Yunxiang Ren, Sui tang and Zhengwei Liu. You guys give me too many helps and joys. I have to say thanks to my wife Suyang Zhao. -
Preduals for Spaces of Operators Involving Hilbert Spaces and Trace
PREDUALS FOR SPACES OF OPERATORS INVOLVING HILBERT SPACES AND TRACE-CLASS OPERATORS HANNES THIEL Abstract. Continuing the study of preduals of spaces L(H,Y ) of bounded, linear maps, we consider the situation that H is a Hilbert space. We establish a natural correspondence between isometric preduals of L(H,Y ) and isometric preduals of Y . The main ingredient is a Tomiyama-type result which shows that every contractive projection that complements L(H,Y ) in its bidual is automatically a right L(H)-module map. As an application, we show that isometric preduals of L(S1), the algebra of operators on the space of trace-class operators, correspond to isometric preduals of S1 itself (and there is an abundance of them). On the other hand, the compact operators are the unique predual of S1 making its multiplication separately weak∗ continuous. 1. Introduction An isometric predual of a Banach space X is a Banach space F together with an isometric isomorphism X =∼ F ∗. Every predual induces a weak∗ topology. Due to the importance of weak∗ topologies, it is interesting to study the existence and uniqueness of preduals; see the survey [God89] and the references therein. Given Banach spaces X and Y , let L(X, Y ) denote the space of operators from X to Y . Every isometric predual of Y induces an isometric predual of L(X, Y ): If Y =∼ F ∗, then L(X, Y ) =∼ (X⊗ˆ F )∗. Problem 1.1. Find conditions on X and Y guaranteeing that every isometric predual of L(X, Y ) is induced from an isometric predual of Y . -
Tight Wavelet Frame Construction and Its Application for Image Processing
Tight Wavelet Frame Construction and its application for Image Processing by Kyunglim Nam (Under the direction of Ming-Jun Lai) Abstract As a generalized wavelet function, a wavelet frame gives more rooms for different construc- tion methods. In this dissertation, first we study two constructive methods for the locally supported tight wavelet frame for any given refinable function whose Laurent polynomial satisfies the QMF or the sub-QMF conditions in Rd. Those methods were introduced by Lai and St¨ockler. However, to apply the constructive method under the sub-QMF condition we need to factorize a nonnegative Laurent polynomial in the multivariate setting into an expression of a finite square sums of Laurent polynomials. We find an explicit finite square sum of Laurent polynomials that expresses the nonnegative Laurent polynomial associated with a 3-direction or 4-direction box spline for various degrees and smoothness. To facilitate the description of the construction of box spline tight wavelet frames, we start with B-spline tight wavelet frame construction. For B-splines we find the sum of squares form by using Fej´er-Rieszfactorization theorem and construct tight wavelet frames. We also use the tensor product of B-splines to construct locally supported bivariate tight wavelet frames. Then we explain how to construct box spline tight wavelet frames using Lai and St¨ockler’s method. In the second part of dissertation, we apply some of our box spline tight wavelet frames for edge detection and image de-noising. We present a lot of images to compare favorably with other edge detection methods including orthonormal wavelet methods and six engineering methods from MATLAB Image Processing Toolbox. -
The Complex Shearlet Transform and Applications to Image Quality Assessment
Technische Universität Berlin Fachgruppe Angewandte Funktionalanalysis The Complex Shearlet Transform and Applications to Image Quality Assessment Master Thesis by Rafael Reisenhofer 18. Juli 2014 – 17. Oktober 2014 Primary reviewer: Prof. Dr. Gitta Kutyniok Secondary reviewer: Dr. Wang-Q Lim Supervisor: Prof. Dr. Gitta Kutyniok Rafael Reisenhofer Beusselstraße 64 10553 Berlin Hiermit erkläre ich, dass ich die vorliegende Arbeit selbstständig und eigenhändig sowie ohne unerlaubte fremde Hilfe und ausschließlich unter Verwendung der aufgeführten Quellen und Hilfsmittel angefertigt habe. Berlin, den 17. Oktober 2014 Rafael Reisenhofer Contents List of Figures 5 1 Introduction 7 2 Complex Shearlet Transforms 9 2.1 From Fourier to Shearlets via an Analysis of Optimality . ........ 10 2.1.1 FourierAnalysis........................... 14 2.1.2 Wavelets............................... 20 2.1.2.1 Wavelets in Two Dimensions . 26 2.1.3 Shearlets............................... 27 2.2 Wavelet and Shearlet Transforms . 33 2.3 Complex Wavelet and Shearlet Transforms . ... 34 3 Complex Shearlet Transforms and the Visual Cortex 41 4 Applications 45 4.1 EdgeDetection ............................... 45 4.1.1 PhaseCongruency ......................... 47 4.1.2 Detection of Singularities With Pairs of Symmetric and Odd- SymmetricWavelets ........................ 51 4.1.3 Edge Detection With Pairs of Symmetric and Odd-Symmetric Shearlets............................... 56 4.2 ImageQualityAssessment . 62 4.2.1 Structural Similarity Index (SSIM) . 63 4.2.2 Complex Shearlet-Based Image Similarity Measure . .... 67 4.2.3 NumericalResults ......................... 71 5 Discussion 75 A Some Definitions and Formulas 79 A.1.1 PolynomialDepthSearch . 81 References 83 3 4 List of Figures 2.1 A piecewise smooth function and a cartoon like image . ...... 11 2.2 ExampleofFouriermodes. -
Operators and Frames
OPERATORS AND FRAMES JAMESON CAHILL, PETER G. CASAZZA AND GITTA KUTYNIOK Abstract. Hilbert space frame theory has applications to various areas of pure mathematics, applied mathematics, and engineering. However, the ques- tion of how applying an invertible operator to a frame changes its properties has not yet been satisfactorily answered, and only partial results are known to date. In this paper, we will provide a comprehensive study of those questions, and, in particular, prove characterization results for (1) operators which gen- erate frames with a prescribed frame operator; (2) operators which change the norms of the frame vectors by a constant multiple; (3) operators which generate equal norm nearly Parseval frames. 1. Introduction To date, Hilbert space frame theory has broad applications in pure mathe- matics, see, for instance, [11, 8, 5], as well as in applied mathematics, computer science, and engineering. This includes time-frequency analysis [15], wireless communication [16, 20], image processing [19], coding theory [21], quantum mea- surements [14], sampling theory [13], and bioimaging [18], to name a few. A fundamental tool in frame theory are the analysis, synthesis and frame operators associated with a given frame. A deep understanding of these operators is indeed fundamental to frame theory and its applications. Let us start by recalling the basic definitions and notions of frame theory. M Given a family of vectors ffigi=1 in an N-dimensional Hilbert space HN , we say M that ffigi=1 is a frame if there exist constants 0 < A ≤ B < 1 satisfying that M 2 X 2 2 Akfk ≤ jhf; fiij ≤ Bkfk for all f 2 HN : i=1 The numbers A; B are called lower and upper frame bounds (respectively) for M the frame. -
S0002-9947-1980-0570783-0.Pdf
transactions of the american mathematical society Volume 260, Number 1, July 1980 NONSTANDARD EXTENSIONS OF TRANSFORMATIONS BETWEEN BANACH SPACES BY D. G. TACON Abstract. Let X and Y be (infinite-dimensional) Banach spaces and denote their nonstandard hulls with respect to an Nj -saturated enlargement by X and Y respectively. If 9> (X, Y) denotes the space of bounded linear transformations then a subset S of elements of ® (X, Y) extends naturally to a subset S of *$>(X, Y). This paper studies the behaviour of various kinds of transformations under this extension and introduces, in this context, the concepts of super weakly compact, super strictly singular and socially compact operators. It shows that (® (X, Y))~ c 'S (X, Y) provided X and Y are infinite dimensional and contrasts this with the inclusion %(H) c (%(H))~ where %(H) denotes the space of compact operators on a Hubert space. The nonstandard hull of a uniform space was introduced by Luxemburg [14] and the construction, in the case of normed spaces, has since been investigated in a number of papers (see, for example [4], [6], [7], [8], [9], [10], [15]). Our intention here is to examine the behaviour of single bounded linear transformations and classes of bounded linear transformations under the nonstandard hull extension. We recount the principal ideas. Consider a normed space (X, || • ||) embedded in a set theoretical structure 911 and consider an N, -sa tura ted enlargement *91t of 9H. An element p G *X is said to be finite if *||p|| is a finite element of *R, the set of such elements being denoted by fin(*Ar).