Buch, Englisch, 472 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 873 g
Analytic and Geometric Aspects
Buch, Englisch, 472 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 873 g
Reihe: Lecture Notes in Pure and Applied Mathematics
ISBN: 978-0-8247-9208-4
Verlag: Routledge
Providing complete expository and research papers on the geometric and analytic aspects of Fourier analysis, this work discusses new approaches to classical problems in the theory of trigonometric series, singular integrals/pseudo-differential operators, Fourier analysis on various groups, numerical aspects of Fourier analysis and their applications, wavelets and more.
Zielgruppe
Professional
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
HP and Weak HP Continuity of Calderon-Zygmund Operators; Ergodic and Mixing Properties of Radial Measures on the Heisenberg Group; A New, Harder Proof That Continuous Functions with Schwartz Derivative 0 are Lines; Integrability of Multiple Series; Aspects of Harmonic Analysis on Real Hyperbolic Space; Trace Theorems Via Wavelets on the Closed Set [0,1]; Meta-Heisenberg Groups; Numerical Approximation of Singular Spectral Functions Arising from the Fourier-Jacobi Problem on a Half Line with Continuous Spectra; Using Sums of Squares to Prove That Certain Entire Functions Have Only Real Zeros; An Application of Coxeter Groups into the Construction of Wavelet Bases in Rn; The Uniform Invertibility of Fourier Transforms of Compositions of Functions in U(R2) with Certain Quadratic Maps of R2; On Methods of Fourier Analysis, in Multigrid Theory; Orthogonal Wavelet Bases for L2 (Rn); Approximation Solvability on Nonlinear Equations and Applications; The Fourier Transform of Tempered Bohemians Homogeneous Cones and Homogeneous Integrals; Fourier Inversion in the Piecewise Smooth Category; Normal Linear Spaces of Trigonometric Transforms and Functions Analytic in the Unit Disk; Fourier and Trigonometric Transforms and Functions Analytic in the Unit Disk; Fourier and Trigonometric Transforms with Complex Coefficients Regularly Varying in Mean; Sampling and the Multisensor Deconvolution Problem.