We use the theory of the continuous wavelet transform to derive inversion formulas for the Radon transform on L 1 \L 2 (R d). These inversion formulas turn out to be local in even dimensions in the following sense. In order to recover a function f from its Radon transform in a ball of radius R > 0 about a point x to within error , we can nd () > 0 such that this can be accomplished by knowing t...

This paper gives necessary conditions and slightly stronger sufficient conditions for a holomorphic function to be the Segal-Bargmann transform of a function in L(R, ρ), where ρ is a Gaussian measure. The proof relies on a family of inversion formulas for the Segal-Bargmann transform, which can be “tuned” to give the best estimates for a given value of p. I also give a single necessary-and-suff...

In this paper, we establish real Paley-Wiener theorems for the Dunkl transform on IR d. More precisely, we characterize the functions in the Schwartz space S(IR d) and in L 2 k (IR d) whose Dunkl transform has bounded, unbounded, convex and nonconvex support. 1 Introduction In the last few years there has been a great interest to real Paley-Wiener theorems for certain integral transforms, see [...

We present a new way of obtaining the Bargmann transform between L 2 (R n) and the Fock space F = F(C n) via a simple restriction principle applied to holo-morphic functions. This same principle also recovers the transform between functions on a compact Lie group and holomorphic functions on its complexii-cation studied by Gross, Hall, Hijab et al., see 1] and 2], and it gives in a similar way ...

The fractional Fourier transforms (FrFTs) is one-parametric family of unitary transformations {F} α=0. FrFTs found a lot of applications in signal and image processing. The identical and classical Fourier transformations are both the special cases of the FrFTs. They correspond to α = 0 (F = I) and α = π/2 (F = F), respectively. Up to now, the fractional Fourier spectra Fi = Fi {f} , i = 1, 2, ....

The discrete wavelet transform has been an exciting topic of mathematical research for about 10 years now. Some of the early wavelet research had seismic applications explicitly in mind, but elds as diverse as quantum physics and voice coding have also provided insights leading to the development of the modern theory. Our purpose is to explain and illustrate the eeect of the discrete wavelet tr...

The wavelet transform of a function f(t) is deened by the formula: Wf(t; a) = W a f(t) = 1 p a Z f(s)g(t ? s a) ds where g(t) is a xed function, t 2 R and a 2 R +. This transform yields a joint timescale representation the original input function that has been of great recent interest. (See for example D1] D2] and HW]). In a recent correspondence, Flandrin F] proposed the use of the wavelet tra...

In a series of papers, we suggested non-statistical method for the detection structural breaks in time series. It is based on applications special fuzzy modeling methods, namely Fuzzy transform (F-transform) and selected methods Natural Logic (FNL). this paper, combine our with principles classical Chow test, which well-known statistical testing presence break. The idea to construct statistics ...

This paper describes an implementation of the Discrete Fourier Transform (DFT) and the Inverse Discrete Fourier Transform (IDFT). We show how the computation of the DFT and IDFT may be performed in Java and show why such operations are typically considered slow. This is a multi-part paper, in part 2, we discuss a speed up of the DFT and IDFT using a class of algorithms known as the FFT (Fast Fo...

We develop an analytic approach to the Radon transform f̂(ζ) = ∫ τ⊂ζ f(τ), where f(τ) is a function on the affine Grassmann manifold G(n, k) of k-dimensional planes in Rn, and ζ is a k′-dimensional plane in the similar manifold G(n, k′), k′ > k. For f ∈ Lp(G(n, k)), we prove that this transform is finite almost everywhere on G(n, k′) if and only if 1 ≤ p < (n− k)/(k′− k), and obtain explicit inv...