Christopher Heil (ed.)

Harmonic Analysis and Applications

In Honor of John J. Benedetto
Ed. by Christopher Heil

• Gebundenes Buch

Produktbeschreibung

This volume, in honor of John J. Benedetto on the occasion of his 65th birthday, features invited articles covering a wide range of topics in areas where he has made fundamental and lasting contributions, such as harmonic analysis, number theory, weighted norm inequalities, wavelet theory, time-frequency analysis, and sampling theory.
Although the scope of the book is broad, chapters are clustered by topic to provide authoritative expositions that will be of lasting interest. The original papers collected here are written by prominent, well-respected researchers and professionals in the field.

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Produktdetails

• Applied and Numerical Harmonic Analysis
• Verlag: Springer, Basel
• Artikelnr. des Verlages: 10968482
• 2006
• Seitenzahl: 374
• Erscheinungstermin: 13. Juli 2006
• Englisch
• Abmessung: 244mm x 164mm x 24mm
• Gewicht: 690g
• ISBN-13: 9780817637781
• ISBN-10: 0817637788
• Artikelnr.: 14731104

Autorenporträt

Christopher Heil, Georgia Institute of Technology, Atlanta, GA, USA

Inhaltsangabe

Foreword.- Preface.- The Benedetto Mathematical Family Tree.- Publications of John J. Benedetto.- Part I. Harmonic Analysis.- The Gibbs Phenomenon in Higher Dimensions.- Weighted Sobolev Inequalities for Gradients.- Semidiscrete Multipliers.- Part II. Frame Theory.- A Physical Interpretation of Tight Frames.- Part III. Time-Frequency Analysis.- Recent Developments in the Balian Low Theorem.- Some Problems Related to the Distributional Zak Transform.- Gabor Duality Characterizations.- A Pedestrian's Approach to Pseudodifferential Operators.- Linear Independence of Finite Gabor Systems.- Part IV. Wavelet Theory.- Explicit Cross-Sections of Singly Generated Group Actions.- The Theory of Wavelets with Composite Dilations.- Part V. Sampling Theory and Shift-Invariant Spaces.- Periodic Nonuniform Sampling in Shift-Invariant Spaces.- Sampling on Unions of Shifted Lattices in One Dimension.- Learning the Right Model from the Data.- Redundancy in the Frequency Domain.- Density Results for