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Pseudo-Differential Operators, Generalized Functions and Asymptotics

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Cover of 'Pseudo-Differential Operators, Generalized Functions and Asymptotics'

Table of Contents

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    Book Overview
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    Chapter 1 Elliptic Theory for Operators Associated with Diffeomorphisms of Smooth Manifolds
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    Chapter 2 The Singular Functions of Branching Edge Asymptotics
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    Chapter 3 The Heat Kernel and Green Function of the Sub-Laplacian on the Heisenberg Group
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    Chapter 4 Metaplectic Equivalence of the Hierarchical Twisted Laplacian
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    Chapter 5 The Heat Kernel and Green Function of a Sub-Laplacian on the Hierarchical Heisenberg Group
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    Chapter 6 L p -bounds for Pseudo-differential Operators on the Torus
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    Chapter 7 Multiplication Properties in Gelfand–Shilov Pseudo-differential Calculus
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    Chapter 8 Operator Invariance
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    Chapter 9 Initial Value Problems in the Time-Frequency Domain
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    Chapter 10 Polycaloric Distributions and the Generalized Heat Operator
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    Chapter 11 Smoothing Effect and Fredholm Property for First-order Hyperbolic PDEs
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    Chapter 12 A Note on Wave-front Sets of Roumieu Type Ultradistributions
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    Chapter 13 Pseudo-Differential Operators, Generalized Functions and Asymptotics
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    Chapter 14 Asymptotically Almost Periodic Generalized Functions
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    Chapter 15 Wave Equations and Symmetric First-order Systems in Case of Low Regularity
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    Chapter 16 Concept of Delta-shock Type Solutions to Systems of Conservation Laws and the Rankine–Hugoniot Conditions
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    Chapter 17 Classes of Generalized Functions with Finite Type Regularities
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    Chapter 18 The Wave Equation with a Discontinuous Coefficient Depending on Time Only: Generalized Solutions and Propagation of Singularities
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    Chapter 19 Generalized Solutions of Abstract Stochastic Problems
  21. Altmetric Badge
    Chapter 20 Nonhomogeneous First-order Linear Malliavin Type Differential Equation
Attention for Chapter 13: Pseudo-Differential Operators, Generalized Functions and Asymptotics
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Chapter title
Pseudo-Differential Operators, Generalized Functions and Asymptotics
Chapter number 13
Book title
Pseudo-Differential Operators, Generalized Functions and Asymptotics
Published in
arXiv, January 2017
DOI 10.1007/978-3-0348-0585-8_13
Book ISBNs
978-3-03-480584-1, 978-3-03-480585-8
Authors

Evelina Erlacher, Michael Grosser

Editors

Shahla Molahajloo, Stevan Pilipović, Joachim Toft, M. W. Wong

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 67%
Student > Bachelor 1 33%
Researcher 1 33%
Readers by discipline Count As %
Physics and Astronomy 2 67%
Computer Science 1 33%
Mathematics 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 January 2017.
All research outputs
#17,855,900
of 22,931,367 outputs
Outputs from arXiv
#441,241
of 941,533 outputs
Outputs of similar age
#294,184
of 421,326 outputs
Outputs of similar age from arXiv
#8,850
of 16,565 outputs
Altmetric has tracked 22,931,367 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 941,533 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 421,326 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16,565 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.