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Pseudo‐differential operators

Communications on Pure and Applied Mathematics, 1965
Contents: Second Order Elliptic Operators.- Pseudo-Differential Operators.- Elliptic Operators on a Compact Manifold without Boundary.- Boundary Problems for Elliptic Differential Operators.- Symplectic Geometry.- Some Classes of (Micro-)Hypoelliptic Operators.- The Strictly Hyperbolic Cauchy Problem.- The Mixed Dirichlet-Cauchy Problem for Second ...
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Differential Operators

2015
In this chapter we study a number of well-known differential operators, which are familiar from the studies of basic calculus, using the framework and terminology of the tensor analysis. We study the Hamiltonian ∇-operator, gradient of scalars, divergence of vectors and tensors, curl of vectors, and Laplacian of scalars and tensors.
M. Dalarsson, N. Dalarsson
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Self-adjoint Boundary Conditions for the Prolate Spheroid Differential Operator

, 2016
We consider the formal prolate spheroid differential operator on a finite symmetric interval and describe all its self-adjoint boundary conditions. Only one of these boundary conditions corresponds to a self-adjoint differential operator which commute ...
V. Katsnelson
semanticscholar   +1 more source

Vector Differential Operators

2021
This chapter covers the mathematical objects: scalar and vector fields, and the three vector differential operators: grad, div and curl. It begins with an overview of scalar and vector fields, followed by the gradient of a scalar field, the divergence and curl of a vector field.
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On the exponential solution of differential equations for a linear operator

, 1954
The present investigation was stimulated by a recent paper of K. 0. Friedrichs 113, who arrived at some purely algebraic problems in connection with the theory of linear operators in quantum mechanics.
W. Magnus
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Differential Operators and Regression

2002
We give statistical evidence from 28 performances of Schumann’s “Traumerei”, as measured by Bruno Repp [886] that the rhythmic, motivic, and harmonic analyses provided by RUBATO® are shaping structures for the agogical streams. The statistical model is based on regression analysis and realizes shaping of agogics by a second degree linear differential ...
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