Programming for Engineers [recurso electrónico] : A Foundational Approach to Learning C and Matlab / by Aaron R. Bradley.

Por: Bradley, Aaron R [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: Texto

TextoEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Descripción: XIV, 238 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642233036Tema(s): Computer science | Software engineering | Data structures (Computer science) | Computer engineering | Computer Science | Software Engineering/Programming and Operating Systems | Electrical Engineering | Data Structures, Cryptology and Information Theory | Mathematics of ComputingFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 005.1 Clasificación LoC:QA76.758Recursos en línea: Libro electrónico Texto

Contenidos:

Chap. 1, Memory: The Stack -- Chap. 2, Control -- Chap. 3, Arrays and Strings -- Chap. 4, Debugging -- Chap. 5, I/O -- Chap. 6, Memory: The Heap -- Chap. 7, Abstract Data Types -- Chap. 8, Linked Lists -- Chap. 9, Introduction to Matlab -- Chap. 10, Exploring ODEs with Matlab -- Chap. 11, Exploring Time and Frequency Domains with Matlab -- Chap. 12, Index.

En: Springer eBooksResumen: To learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field. The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know. The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.

Existencias ( 1 )
Notas de título ( 3 )

Existencias
Tipo de ítem	Biblioteca actual	Colección	Signatura	Copia número	Estado	Fecha de vencimiento	Código de barras
Libro Electrónico	Biblioteca Electrónica	Colección de Libros Electrónicos	QA76.758 (Browse shelf(Abre debajo))	1	No para préstamo		376631-2001

To learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field. The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know. The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.