Name: Mechanics and Dynamical Systems with Mathematica(r) (en Inglés)
Price: 325.12 PEN
Availability: InStock
Author: Bellomo, Nicola ; Preziosi, Luigi ; Romano, Antonio
ISBN: 9781461271017

portada Mechanics and Dynamical Systems with Mathematica(r) (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

417

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 2.3 cm

Peso

0.61 kg.

ISBN13

9781461271017

Categorías

Mecánica clásica
Ingeniería mecánica

Mechanics and Dynamical Systems with Mathematica(r) (en Inglés)

Nicola Bellomo (Autor) · Antonio Romano (Autor) · Luigi Preziosi (Autor) · Birkhauser · Tapa Blanda

Libro Nuevo

S/ 325,12

S/ 541,87

Ahorras: S/ 216,75

40% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Viernes 19 de Julio y el Martes 30 de Julio.

Lo recibirás en cualquier lugar de Perú entre 2 y 5 días hábiles luego del envío.

Reseña del libro "Mechanics and Dynamical Systems with Mathematica(r) (en Inglés)"

Modeling and Applied Mathematics Modeling the behavior of real physical systems by suitable evolution equa- tions is a relevant, maybe the fundamental, aspect of the interactions be- tween mathematics and applied sciences. Modeling is, however, only the first step toward the mathematical description and simulation of systems belonging to real world. Indeed, once the evolution equation is proposed, one has to deal with mathematical problems and develop suitable simula- tions to provide the description of the real system according to the model. Within this framework, one has an evolution equation and the re- lated mathematical problems obtained by adding all necessary conditions for their solution. Then, a qualitative analysis should be developed: this means proof of existence of solutions and analysis of their qualitative be- havior. Asymptotic analysis may include a detailed description of stability properties. Quantitative analysis, based upon the application ofsuitable methods and algorithms for the solution of problems, ends up with the simulation that is the representation of the dependent variable versus the independent one. The information obtained by the model has to be compared with those deriving from the experimental observation of the real system. This comparison may finally lead to the validation of the model followed by its application and, maybe, further generalization.