This volume consists of papers inspired by the special session on pseudo-differential operators at the 10th ISAAC Congress held at the University of Macau, August 3-8, 2015 and the mini-symposium on pseudo-differential operators in industries and technologies at the 8th ICIAM held at the National Convention Center in Beijing, August 10-14, 2015.
The twelve papers included present cutting-edge trends in pseudo-differential operators and applications from the perspectives of Lie groups (Chapters 1-2), geometry (Chapters 3-5) and applications (Chapters 6-12). Many contributions cover applications in probability, differential equations and time-frequency analysis. A focus on the synergies of pseudo-differential operators with applications, especially real-life applications, enhances understanding of the analysis and the usefulness of these operators.
Series
Edition
Softcover reprint of the original 1st ed. 2017
Language
Place of publication
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
12 s/w Abbildungen, 11 farbige Abbildungen
VIII, 239 p. 23 illus., 11 illus. in color.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
ISBN-13
978-3-319-83754-3 (9783319837543)
DOI
10.1007/978-3-319-47512-7
Schweitzer Classification
Pseudo-Differential Operators on the Affine Group.- Pseudo-Differential Operators on Non-Isotropic Heisenberg Groups with Multi-Dimensional Center.- Curvatures of the Heisenberg Group.- Ellipticity with Global Projection Conditions.- Multilinear Localization Operators Associated to Quaternion Fourier Transforms.- A Time-Frequency Relationship between the Langevin Equation and the Harmonic Oscillator.- Are There Quantum Operators and Wave Functions in Standard Probability Theory.- A Class of Non-Markovian Pseudo-Differential Operators of Lévy Type.- On the Solvability of Some Systems of Integro-Differential Equations with Anomalous Diffusion.- Visualizing Discrete Complex-Valued Time-Frequency Representations.- The Reassigned Spectrogram of the Stockwell transform.- Continuous Multi-Wavelet Transforms for Blind Signal Separation.
