Catálogo de publicaciones - libros
Qualitative Methods in Inverse Scattering Theory: An Introduction
Fioralba Cakoni David Colton
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Analysis; Appl.Mathematics/Computational Methods of Engineering; Applications of Mathematics; Continuum Mechanics and Mechanics of Materials; Optics and Electrodynamics; Electrical Engineering
Disponibilidad
| Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | 2006 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-540-28844-2
ISBN electrónico
978-3-540-31230-7
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2006
Información sobre derechos de publicación
© Springer-Verlag Berlin Heidelberg 2006
Cobertura temática
Tabla de contenidos
Functional Analysis and Sobolev Spaces
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 1-25
Ill-Posed Problems
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 27-43
Scattering by an Imperfect Conductor
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 45-60
The Inverse Scattering Problem for an Imperfect Conductor
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 61-80
Scattering by an Orthotropic Medium
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 81-104
The Inverse Scattering Problem for an Orthotropic Medium
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 105-129
The Factorization Method
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 131-152
Mixed Boundary Value Problems
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 153-212
A Glimpse at Maxwell’s Equations
Fioralba Cakoni; David Colton
is used to assess catastrophic risk and to improve risk management strategies (Grossi, Kunreuther and Windeler 2005: 27). The modeling of catastrophe risk is a complex process that depends on subjective and objective inputs related to the natural hazard. After the catastrophe model is built usually it is too complex to be evaluated analytically, especially if long term economic consequences are considered. In a a computer is used to evaluate a model numerically, and data are gathered in order to estimate the characteristics of the model (Law and Kelton 1991: 1). Usually catastrophe modeling implicitly incorporates simulations due to the sheer complexity of the system to be analyzed. Catastrophe modeling and simulation have advantages as well as limitations. Some of them are presented below.
Pp. 213-218