Appendix A. Special Cases of the Marcinkiewicz Interpolation Theorem

Total Page:16

File Type:pdf, Size:1020Kb

Appendix A. Special Cases of the Marcinkiewicz Interpolation Theorem Appendix A. Special Cases of the Marcinkiewicz Interpolation Theorem In a number of places in Chapters 2, 3 and 5, we employ simple forms of the Marcinkiewicz interpolation theorem. The purpose of this appendix is to present for the reader's convenience statements and proofs of the theorems involved and to explain the concepts associated with them. More general versions of the Mar­ cinkiewicz theorem can be found in [9], Section 13.8 and [33], Appendix B. Let us agre'e that the measure spaces appearing below are always (J-finite. A.I. The Concepts of Weak Type and Strong Type A.I.t. Strong type. Let (M, JIt, 11) and (N, .AI, v) be measure spaces and p an index in the range [1, ex)]. Suppose D is a subset of V(Il) and T is a mapping from D into the space of complex-valued measurable functions on N, or the space of nonnegative extended-real-valued measurable functions on N, or the space of equiv­ alence classes of one of these. We say T is of strong type (p, p), or simply of type (p, p), on D if there is a constant B such that (1) for allfin D. The smallest number B for which (1) holds is then termed the (p, p) norm of Ton D and is denoted II TIIp,p, when D is understood. Even if there may not exist a finite constant B for which (1) holds, it is customary to define (provided of course that D #- {On. So we may say that T is of type (p, p) on D if and only if IITllp,p < 00. A.t.2. Remarks. (i) In practice, D is usually a linear subspace of V(Il) , T takes its values in the space of complex measurable functions on N, and is linear. (ii) Our concern in the text is mostly with operators T of the form T.p intro­ duced in 1.2.2 and 2.4.1. The operators T.p are viewed as having the initial domain L2(G) and range in L2(G), G being an arbitrary LCA group. Our main interest is in knowing whether, when 1 :::;; p :::;; 00 and T.p is restricted to D = L2 n V(G), 178 App:mdix A. Special Cases of the Marcinkiewicz Interpolation Theorem T", is of type (p, p) on D; in several instances, it is the value of II T",llp,p which is more important. (iii) The definition of strong type is clearly D-dependent, in general. However, in most practical instances, this poses no difficulty. To illustrate the point, suppose cJ> E ,!l'OO(X), X being the dual group of G, T = T", and T is of type (p, p) on D. Suppose that D is a linear subspace of L2 n U(G) and that for every I in L2 n U(G) there exists a sequence (/,,) extracted from D such that lim II/" - 1112 = 0 and lim II/"Ilp ~ 1I/11p. (2) 1 (D = L n L 00 (G) for example). Then if (1) holds for every lin D, it continues to hold for every lin L2 n U(G). To see this, suppose IE L 2 n U(G) and that (/,,) is as above. Since /" -+ I in L2(G) and every operator T", is continuous on L2(G) (cf. 1.2.2), it follows that T/" -+ Tlin L2(G). Hence there is a subsequence (T/,,) which converges pointwise a.e. to Tf Now II Tilip ~ lim inf II T/")Ip (3) j-+ 00 by Fatou's lemma if p < 00, and trivially otherwise. Since T is of type (p, p) on D, (4) for allj; combining (2), (3) and (4), we deduce that Tis of type (p,p) on L2 n U(G). In the same way, Tis continuously extendable into an operator of type (p,p) on U(G). A.l.3. Weak type. Let T and D be as in A.U, and denote by A.T! the dis­ tribution function of ITII; that is, define, for t > 0, A.T/t) = v({y E N: ITI(y) I > t}). If p < 00, we say Tis 01 weak type (p, p) on D if there is a nonnegative real number A such that (5) for allfin D and all t > O. If there exist such numbers A, there is a smallest, called the weak (p, p) norm 01 T on D. If no such number exists, the weak (p, p) norm of Ton D is set equal to 00. The mapping T is said to be 01 weak type (00, 00) on D if and only if it is of type (00,00) on D; its weak (00,00) norm is declared to be the same as its (00, 00) norm. It is very simple to see that a mapping T of type (p, p) on D is also of weak type there, but the converse is false, unless of course p = 00. A.l.4. Remark. The choice of D is again to some extent immaterial. For A.2. The Interpolation Theorems 179 instance, suppose that p E [1, (0), T = Tq" D is as in A. I .2(iii) and that (5) holds for all f in D and all t > O. Then (5) holds for all f in L 2 (") U(G). To see this, adopt the notation of A. I .2(iii). Then {y: ITf(y) I > t} ~ u n {y: ITf,,/y) I > t} i j~j and hence ATlt) ~ lim v(n {y: ITf,,/y) I > t}) i-+oo j~i ::>; liminfv({y: ITf,,/y) I > t}) j-+ 00 ::>; li~ inf APt-PIIf,,)I~ J-+ co At this point, it is possible to go one step further and extend Tfrom L2 (") U(G) into a mapping from LP(G) into the set of classes of measurable functions in such a way that (5) continues to hold for every fin U(G). For, givenfin U(G), select any sequence (f,,) from L2 (") U(G) converging in U to! Write gn for any function of the class Tf". Then (5) shows that the sequence (gn) is Cauchy in measure and therefore converges in measure to some function g. It also follows from (5) that the class of g does not depend on the choice of the sequence (f,,) (provided f" -+ f in U(G), of course). So we may define Tfto be the class of g. Once again, there is a subsequence (gn) converging a.e. to g and so the same argument as before leads to (5). It follows from (5) that Tf, although it may not belong to U(G), does belong locally to Lq(G) for every q < p ([9], Exercise 13.16). A.2. The Interpolation Theorems Letfbe a measurable function and t > O. Denote by ft andr the following func­ tions. ft(x) = {f(oX) if If(x) I ::>; t otherwise ff(x) if If(x) I > t rcx) = \ 0 l otherwise. With this notation fixed, we can state and prove the first theorem. A.2.t. Theorem (Marcinkiewicz). Suppose that r E (1, (0), D is a linear sub­ space of L 1 (") L'(M) and T is an operator mapping D into the set of equivalence 180 Appendix A. Special Cases of the Marcinkiewicz Interpolation Theorem classes of complex measurable functions or of nonnegative extended-real-valued measurable functions on N. Assume that D and T satisfy the following conditions. (i) !ffE D and t > 0, thenfr andp are in D. (ii) Tis subadditive in the sense that IT(f + g)1 ~ ITfl + ITgl for f and g in D. (iii) T is of weak type (I, 1) on D with weak (I, 1) norm at most AI' so that (I) for f in D and t > o. (iv) Tis of weak type (r, r) on D with weak (r, r) norm at most A" so that (2) for fin D and t > o. Suppose that 1 < p < r. Then T is of type (p, p) on D and (3) for all fin D, where (4) In other words, the (p, p) norm of T on D is at most Ap. where Ap is given by (4). Proof SupposefE D and t > o. Sincef = fr + p, the subadditivity of T and (i) show that ITfl ~ ITfrl + ITPI, whence it follows that ATAt) ~ very: ITP(y) I > t12}) + very: ITfr(y) I > tI2}). Applying (I) and (2) top andfr respectively, we deduce that 1 r r ATAt) ~ 2A l t- L'P' dl1 + (2ArYt- J)frl dl1 = 2AI r Ifldl1 + 2rA~t-r r Iflrdll. (5) J{x: If(x)1 >t) J{x: If(x>!';;t} Now (6) A.2. The Interpolation Theorems 181 and so we deduce from (5) that + roo tP-l{2'A~t-' rill' dP,}dt Jo J{x: If(x)J .. tl = 2AI rtP-2{LI/(X)Icf>(X, t)dP,(X)}dt + 2'A~ rtP-I-r {L I/(x)I' !/lex, t) dp,(x) }dt, (7) where cf> is the characteristic function of the set E = {(x, t): I/(x) I > t} £ M x (0, (0) and !/l is the characteristic function of the set F = {(x, t): I/(x) I ~ t} £ (M x (0, oo»\E. If (Sft)ft" I is an enumeration of the positive rationals, E = U ({x: I/(x) I > Sft} x (0, Sft», n~l which shows that E is measurable in the pair of variables. The same is therefore true of F and so, by the Fubini theorem (recall that Mis u-finite) we may invert the order of the integrations in (7) to conclude that p-1IlTIII: ~ 2Al L{J~f(X)1 tP-2 dt } I/(x) I dp,(x) + 2r A~ r {rOO t p - I -, dt} I/(x)I' dJl.(x) JM Jlf(X)1 = 2AI L(p - l)-II/(x)IP-II/(x)1 dp,(x) + 2'A~ L(r - p)-ll/(x)lp-rl/(x)I' dp,(x), which is equivalent to (3) and (4).
Recommended publications
  • The Hilbert Transform
    (February 14, 2017) The Hilbert transform Paul Garrett [email protected] http:=/www.math.umn.edu/egarrett/ [This document is http:=/www.math.umn.edu/egarrett/m/fun/notes 2016-17/hilbert transform.pdf] 1. The principal-value functional 2. Other descriptions of the principal-value functional 3. Uniqueness of odd/even homogeneous distributions 4. Hilbert transforms 5. Examples 6. ... 7. Appendix: uniqueness of equivariant functionals 8. Appendix: distributions supported at f0g 9. Appendix: the snake lemma Formulaically, the Cauchy principal-value functional η is Z 1 f(x) Z f(x) ηf = principal-value functional of f = P:V: dx = lim dx −∞ x "!0+ jxj>" x This is a somewhat fragile presentation. In particular, the apparent integral is not a literal integral! The uniqueness proven below helps prove plausible properties like the Sokhotski-Plemelj theorem from [Sokhotski 1871], [Plemelji 1908], with a possibly unexpected leading term: Z 1 f(x) Z 1 f(x) lim dx = −iπ f(0) + P:V: dx "!0+ −∞ x + i" −∞ x See also [Gelfand-Silov 1964]. Other plausible identities are best certified using uniqueness, such as Z f(x) − f(−x) ηf = 1 dx (for f 2 C1( ) \ L1( )) 2 x R R R f(x)−f(−x) using the canonical continuous extension of x at 0. Also, 2 Z f(x) − f(0) · e−x ηf = dx (for f 2 Co( ) \ L1( )) x R R R The Hilbert transform of a function f on R is awkwardly described as a principal-value integral 1 Z 1 f(t) 1 Z f(t) (Hf)(x) = P:V: dt = lim dt π −∞ x − t π "!0+ jt−xj>" x − t with the leading constant 1/π understandable with sufficient hindsight: we will see that this adjustment makes H extend to a unitary operator on L2(R).
    [Show full text]
  • Arxiv:1507.07356V2 [Math.AP]
    TEN EQUIVALENT DEFINITIONS OF THE FRACTIONAL LAPLACE OPERATOR MATEUSZ KWAŚNICKI Abstract. This article discusses several definitions of the fractional Laplace operator ( ∆)α/2 (α (0, 2)) in Rd (d 1), also known as the Riesz fractional derivative − ∈ ≥ operator, as an operator on Lebesgue spaces L p (p [1, )), on the space C0 of ∈ ∞ continuous functions vanishing at infinity and on the space Cbu of bounded uniformly continuous functions. Among these definitions are ones involving singular integrals, semigroups of operators, Bochner’s subordination and harmonic extensions. We collect and extend known results in order to prove that all these definitions agree: on each of the function spaces considered, the corresponding operators have common domain and they coincide on that common domain. 1. Introduction We consider the fractional Laplace operator L = ( ∆)α/2 in Rd, with α (0, 2) and d 1, 2, ... Numerous definitions of L can be found− in− literature: as a Fourier∈ multiplier with∈{ symbol} ξ α, as a fractional power in the sense of Bochner or Balakrishnan, as the inverse of the−| Riesz| potential operator, as a singular integral operator, as an operator associated to an appropriate Dirichlet form, as an infinitesimal generator of an appropriate semigroup of contractions, or as the Dirichlet-to-Neumann operator for an appropriate harmonic extension problem. Equivalence of these definitions for sufficiently smooth functions is well-known and easy. The purpose of this article is to prove that, whenever meaningful, all these definitions are equivalent in the Lebesgue space L p for p [1, ), ∈ ∞ in the space C0 of continuous functions vanishing at infinity, and in the space Cbu of bounded uniformly continuous functions.
    [Show full text]
  • Design and Application of a Hilbert Transformer in a Digital Receiver
    Proceedings of the SDR 11 Technical Conference and Product Exposition, Copyright © 2011 Wireless Innovation Forum All Rights Reserved DESIGN AND APPLICATION OF A HILBERT TRANSFORMER IN A DIGITAL RECEIVER Matt Carrick (Northrop Grumman, Chantilly, VA, USA; [email protected]); Doug Jaeger (Northrop Grumman, Chantilly, VA, USA; [email protected]); fred harris (San Diego State University, San Diego, CA, USA; [email protected]) ABSTRACT A common method of down converting a signal from an intermediate frequency (IF) to baseband is using a quadrature down-converter. One problem with the quadrature down-converter is it requires two low pass filters; one for the real branch and one for the imaginary branch. A more efficient way is to transform the real signal to a complex signal and then complex heterodyne the resultant signal to baseband. The transformation of a real signal to a complex signal can be done using a Hilbert transform. Building a Hilbert transform directly from its sampled data sequence produces suboptimal results due to time series truncation; another method is building a Hilbert transformer by synthesizing the filter coefficients from half Figure 1: A quadrature down-converter band filter coefficients. Designing the Hilbert transform filter using a half band filter allows for a much more Another way of viewing the problem is that the structured design process as well as greatly improved quadrature down-converter not only extracts the desired results. segment of the spectrum it rejects the undesired spectral image, the spectral replica present in the Hermetian 1. INTRODUCTION symmetric spectra of a real signal. Removing this image would result in a single sided spectrum which being non- The digital portion of a receiver is typically designed to Hermetian symmetric is the transform of a complex signal.
    [Show full text]
  • Communication Theory II Slides 04
    Communication Theory II Lecture 4: Review on Fourier analysis and probabilty theory Ahmed Elnakib, PhD Assistant Professor, Mansoura University, Egypt Febraury 19th, 2015 1 Course Website o http://lms.mans.edu.eg/eng/ o The site contains the lectures, quizzes, homework, and open forums for feedback and questions o Log in using your name and password o Password for quizzes: third o One page quiz: for less download time 2 Lecture Outlines o Review on Fourier analysis of signals and systems . The Dirac delta function . Fourier transform of periodic signals . Transmission of signals through LTI systems . Hilbert transform o Review on probability theory . Deterministic vs. probabilistic mathematical models . Probability theory, random variables, and the distribution functions . The concept of expectation and second order statistics . Characteristic function, the center limit theory and the Bayesian interface 3 The Dirac Delta Function (Unit Impulse) δ(t) t 0 o An even function of time t, centered at the origin t = 0 o Sifting property: sifts out the value g(t0) of the function g(t) at time t = t0, where o Replication property: convolution of any function with the delta function leaves that function unchanged 4 The Dirac Delta Function (cont’d) W=1 Amplitude W=2 Amplitude W=5 f(t)=δ(t) F(f)=1 1 t Amplitude 0 0 f5 The Dirac Delta Function (cont’d) T→0 The delta function may be viewed Rectangular impulse as the limiting form of a pulse of unit area (symmetric with respect to the origin) as the duration of the pulse approaches zero Sinc impulse T=1/2W 6 Existence of Fourier Transform o Physical realizability is a sufficient condition for the existence of a Fourier transform (e.g., all energy signals are Fourier transformable ).
    [Show full text]
  • On Some Integral Operators Appearing in Scattering Theory, And
    On some integral operators appearing in scattering theory, and their resolutions S. Richard,∗ T. Umeda† Graduate school of mathematics, Nagoya University, Chikusa-ku, Nagoya 464-8602, Japan Department of Mathematical Sciences, University of Hyogo, Shosha, Himeji 671-2201, Japan E-mail: [email protected], [email protected] Abstract We discuss a few integral operators and provide expressions for them in terms of smooth functions of some natural self-adjoint operators. These operators appear in the context of scattering theory, but are independent of any perturbation theory. The Hilbert transform, the Hankel transform, and the finite interval Hilbert transform are among the operators considered. 2010 Mathematics Subject Classification: 47G10 Keywords: integral operators, Hilbert transform, Hankel transform, dilation operator, scattering theory 1 Introduction Investigations on the wave operators in the context of scattering theory have a long history, and several powerful technics have been developed for the proof of their existence and of their completeness. More recently, properties of these operators in various spaces have been studied, and the importance of these operators for non-linear problems has also been acknowledged. A quick search on MathSciNet shows that the terms wave operator(s) appear in the title of numerous papers, confirming their importance in various fields of mathematics. For the last decade, the wave operators have also played a key role for the arXiv:1909.01712v1 [math-ph] 4 Sep 2019 search of index theorems in scattering theory, as a tool linking the scattering part of a physical system to its bound states. For such investigations, a very detailed ∗Supported by the grantTopological invariants through scattering theory and noncommuta- tive geometry from Nagoya University, and by JSPS Grant-in-Aid for scientific research (C) no 18K03328, and on leave of absence from Univ.
    [Show full text]
  • Arxiv:1611.05269V3 [Cs.IT] 29 Jan 2018 Graph Analytic Signal, and Associated Amplitude and Frequency Modulations Reveal Com
    On Hilbert Transform, Analytic Signal, and Modulation Analysis for Signals over Graphs Arun Venkitaraman, Saikat Chatterjee, Peter Handel¨ Department of Information Science and Engineering, School of Electrical Engineering and ACCESS Linnaeus Center KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden . Abstract We propose Hilbert transform and analytic signal construction for signals over graphs. This is motivated by the popularity of Hilbert transform, analytic signal, and mod- ulation analysis in conventional signal processing, and the observation that comple- mentary insight is often obtained by viewing conventional signals in the graph setting. Our definitions of Hilbert transform and analytic signal use a conjugate-symmetry-like property exhibited by the graph Fourier transform (GFT), resulting in a ’one-sided’ spectrum for the graph analytic signal. The resulting graph Hilbert transform is shown to possess many interesting mathematical properties and also exhibit the ability to high- light anomalies/discontinuities in the graph signal and the nodes across which signal discontinuities occur. Using the graph analytic signal, we further define amplitude, phase, and frequency modulations for a graph signal. We illustrate the proposed con- cepts by showing applications to synthesized and real-world signals. For example, we show that the graph Hilbert transform can indicate presence of anomalies and that arXiv:1611.05269v3 [cs.IT] 29 Jan 2018 graph analytic signal, and associated amplitude and frequency modulations reveal com- plementary information in speech signals. Keywords: Graph signal, analytic signal, Hilbert transform, demodulation, anomaly detection. Email addresses: [email protected] (Arun Venkitaraman), [email protected] (Saikat Chatterjee), [email protected] (Peter Handel)¨ Preprint submitted to Signal Processing 1 1 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 (a) (b) Figure 1: Anomaly highlighting behavior of the graph Hilbert transform for 2D image signal graph.
    [Show full text]
  • Hilbert Transform and Singular Integrals on the Spaces of Tempered Ultradistributions
    ALGEBRAIC ANALYSIS AND RELATED TOPICS BANACH CENTER PUBLICATIONS, VOLUME 53 INSTITUTE OF MATHEMATICS POLISH ACADEMY OF SCIENCES WARSZAWA 2000 HILBERT TRANSFORM AND SINGULAR INTEGRALS ON THE SPACES OF TEMPERED ULTRADISTRIBUTIONS ANDRZEJKAMINSKI´ Institute of Mathematics, University of Rzesz´ow Rejtana 16 C, 35-310 Rzesz´ow,Poland E-mail: [email protected] DUSANKAPERIˇ SIˇ C´ Institute of Mathematics, University of Novi Sad Trg Dositeja Obradovi´ca4, 21000 Novi Sad, Yugoslavia E-mail: [email protected] STEVANPILIPOVIC´ Institute of Mathematics, University of Novi Sad Trg Dositeja Obradovi´ca4, 21000 Novi Sad, Yugoslavia E-mail: [email protected] Abstract. The Hilbert transform on the spaces S0∗(Rd) of tempered ultradistributions is defined, uniquely in the sense of hyperfunctions, as the composition of the classical Hilbert transform with the operators of multiplying and dividing a function by a certain elliptic ultra- polynomial. We show that the Hilbert transform of tempered ultradistributions defined in this way preserves important properties of the classical Hilbert transform. We also give definitions and prove properties of singular integral operators with odd and even kernels on the spaces S0∗(Rd), whose special cases are the Hilbert transform and Riesz operators. 1. Introduction. The Hilbert transform on distribution and ultradistribution spaces has been studied by many mathematicians, see e.g. Tillmann [17], Beltrami and Wohlers [1], Vladimirov [18], Singh and Pandey [15], Ishikawa [2], Ziemian [20] and Pilipovi´c[11]. In all these papers the Hilbert transform is defined by one of the two methods: by the method of adjoints or by considering a generalized function on the kernel which belongs to the corresponding test function space.
    [Show full text]
  • Singular Integrals on Self-Similar Sets and Removability for Lipschitz Harmonic Functions in Heisenberg Groups
    SINGULAR INTEGRALS ON SELF-SIMILAR SETS AND REMOVABILITY FOR LIPSCHITZ HARMONIC FUNCTIONS IN HEISENBERG GROUPS VASILIS CHOUSIONIS AND PERTTI MATTILA Abstract. In this paper we study singular integrals on small (that is, measure zero and lower than full dimensional) subsets of metric groups. The main examples of the groups we have in mind are Euclidean spaces and Heisenberg groups. In addition to obtaining results in a very general setting, the purpose of this work is twofold; we shall extend some results in Euclidean spaces to more general kernels than previously considered, and we shall obtain in Heisenberg groups some applications to harmonic (in the Heisenberg sense) functions of some results known earlier in Euclidean spaces. 1. Introduction The Cauchy singular integral operator on one-dimensional subsets of the complex plane has been studied extensively for a long time with many applications to analytic functions, in particular to analytic capacity and removable sets of bounded analytic functions. There have also been many investigations of the same kind for the Riesz singular integral op- erators with the kernel x=jxj−m−1 on m-dimensional subsets of Rn. One of the general themes has been that boundedness properties of these singular integral operators imply some geometric regularity properties of the underlying sets, see, e.g., [DS], [M1], [M3], [Pa], [T2] and [M5]. Standard self-similar Cantor sets have often served as examples where such results were first established. This tradition was started by Garnett in [G1] and Ivanov in [I1] who used them as examples of removable sets for bounded analytic functions with positive length.
    [Show full text]
  • The Hilbert Transform
    The Hilbert transform 1 Definition and properties 1 Recall the distribution pv( x ), defined by Z '(x) pv(1=x)(') := lim dx: !0 jx|≥ x The Hilbert transform is defined via the convolution with pv(1=x), namely 1 Z f(x − t) (Hf)(x) := lim dt: π !0 jt|≥ t The main theorem we are going to prove in this note is the following. Theorem 1.1. For any p 2 (1; +1), there exists a constant Cp such that kHfkp < Cpkfkp (1.1) for all f 2 S(R). Thus, H extends to a bounded linear operator on all of Lp(R). The first remark we make is that the above theorem is false when p = 1. To see this, note that for smooth f with compact support, when x is very large, the main contribution to the integral Z f(x − t) dt t comes from the values t which are not far away from x. This in general gives the decay 1 rate of order jxj , unless there is a magical cancellation due to the sign changes of f, in which case one can hope for a faster decay. Indeed, it is not hard to show that if f is continuous and has compact support with R f(t)dt = a, then a (Hf)(x) = + O(1=x2) πx 1 R for all large x. As a consequence, Hf 2 L (R) if and only if f = 0. The statement of 1 the above theorem is also not true for p = +1. The reason is that x is not integrable at infinity, so one can not bound on kHfk1 merely by using the maximum of f without any other information (e.g., the size of the support).
    [Show full text]
  • Lecture Notes, Singular Integrals
    Lecture notes, Singular Integrals Joaquim Bruna, UAB May 18, 2016 Chapter 3 The Hilbert transform In this chapter we will study the Hilbert transform. This is a specially important operator for several reasons: • Because of its relationship with summability for Fourier integrals in Lp- norms. • Because it constitutes a link between real and complex analysis • Because it is a model case for the general theory of singular integral op- erators. A main keyword in the theory of singular integrals and in analysis in general is cancellation. We begin with some easy examples of what this means. 3.1 Some objects that exist due to cancellation One main example of something that exists due to cancellation is the Fourier 2 d 2 transform of functions in L (R ). In fact the whole L -theory of the Fourier transform exists thanks to cancellation properties. Let us review for example 1 d 2 d the well-known Parseval's theorem, stating that for f 2 L (R )\L (R ) one has kf^k2 = kfk2, a result that allows to extend the definition of the Fourier 2 d transform to L (R ). Formally, Z Z Z Z jf^(ξ)j2 dξ = f(x)f(y)( e2πiξ·(y−x)dξ)dxdy: Rd Rd Rd Rd This being equal to R jf(x)j2 dx means formally that Rd Z 2πiξ·x e dξ = δ0(x): Rd Along the same lines, let us look at the Fourier inversion theorem, stating 1 d 1 d that whenever f 2 L (R ); f^ 2 L (R ) one has 1 Z f(x) = f^(ξ)e2πiξ·x dξ: Rd Again, the right hand side, by a formal use of Fubini's theorem becomes Z Z Z Z ( f(y)e−2πiξ·y dy)e2πiξ·x dξ = f(y)( e−2πiξ·(y−x) dy) dξ: Rd Rd Rd Rd If this is to be equal to f(x) we arrive to the same formal conclusion, namely that superposition of all frequencies is zero outside zero.
    [Show full text]
  • Discrete Hilbert Transform. Numeric Algorithms
    Volume 49, Number 4, 2008 485 Discrete Hilbert Transform. Numeric Algorithms Gheorghe TODORAN, Rodica HOLONEC and Ciprian IAKAB Abstract - The Hilbert and Fourier transforms are tools used for signal analysis in the time/frequency domains. The Hilbert transform is applied to casual continuous signals. The majority of the practical signals are discrete signals and they are limited in time. It appeared therefore the need to create numeric algorithms for the Hilbert transform. Such an algorithm is a numeric operator, named the Discrete Hilbert Transform. This paper makes a brief presentation of known algorithms and proposes an algorithm derived from the properties of the analytic complex signal. The methods for time and frequency calculus are also presented. 1. INTRODUCTION spectrum in order to avoid the aliasing process – the Nyquist condition. Signals can be classified into two classes: The discrete signal will be analyzed on a analytic signals (for instance = sin)( ωtAtx ), computer system, which implies its and experimental signals (measured signals). digitization (the digital signal is the discrete The last category represents real signals and is signal converted in binary format, accordingly of great importance in applications. to the adopted analog/numeric conversion; in An experimental signal represents a signal most of the cases, the signal acquisition observed during a limited interval of time. It is hardware also does the digitization of the a sample of the original signal, which signal samples). The resulted digital signal has characterizes a physical process of interest. the greatest importance in numeric analysis The experimental signal can be a operations. continuous time signal (analogical), or a Some other remarks need to be made.
    [Show full text]
  • Spectral Decompositions in Banach Spaces and the Hilbert Transform
    LINEAR OPERATORS BANACH CENTER PUBLICATIONS, VOLUME 38 INSTITUTE OF MATHEMATICS POLISH ACADEMY OF SCIENCES WARSZAWA 1997 SPECTRAL DECOMPOSITIONS IN BANACH SPACES AND THE HILBERT TRANSFORM T. A. GILLESPIE Department of Mathematics and Statistics University of Edinburgh, James Clerk Maxwell Building Edinburgh EH9 3JZ, Scotland E-mail: [email protected] Abstract. This paper gives a survey of some recent developments in the spectral theory of linear operators on Banach spaces in which the Hilbert transform and its abstract analogues play a fundamental role. 1. Introduction. Various notions of self-adjointness have been developed for oper- ators acting on Banach spaces, each reflecting some aspect of the Hilbert space theory. One such notion is that of well-boundedness, a concept introduced by Smart [23] and first studied by Smart and Ringrose [21–23]. An operator is (by definition) well-bounded if it has a functional calculus based on the Banach algebra of absolutely continuous func- tions on a compact real interval. This functional calculus gives rise to a form of spectral diagonalization, as will be described in more detail below. Initially, there were relatively few examples of well-bounded operators, other than rather obvious ones, until Dowson and Spain [17] gave an interesting example of a well- bounded operator A acting on Lp(Z) for p in the range 1 <p< ∞. It can be shown that the operator they considered has the property that eiA is the bilateral shift on Lp(Z) (see [18, p. 1044]) and this observation illustrates the more general fact [19] that every translation operator on Lp(G), where G is a locally compact abelian group and 1 <p< ∞, is of the form eiA for some well-bounded operator A.
    [Show full text]