Evolutionary Algorithms for Embedded System Design [electronic resource] /

Evolutionary Algorithms for Embedded System Design describes how Evolutionary Algorithm (EA) concepts can be applied to circuit and system design - an area where time-to-market demands are critical. EAs create an interesting alternative to other approaches since they can be scaled with the problem size and can be easily run on parallel computer systems. This book presents several successful EA techniques and shows how they can be applied at different levels of the design process. Starting on a high-level abstraction, where software components are dominant, several optimization steps are demonstrated, including DSP code optimization and test generation. Throughout the book, EAs are tested on real-world applications and on large problem instances. For each application the main criteria for the successful application in the corresponding domain are discussed. In addition, contributions from leading international researchers provide the reader with a variety of perspectives, including a special focus on the combination of EAs with problem specific heuristics. Evolutionary Algorithms for Embedded System Design is an excellent reference for both practitioners working in the area of circuit and system design and for researchers in the field of evolutionary concepts.

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Bibliographic Details
Main Authors: Drechsler, Rolf. editor., Drechsler, Nicole. editor., SpringerLink (Online service)
Format: Texto biblioteca
Language:eng
Published: Boston, MA : Springer US : Imprint: Springer, 2003
Subjects:Engineering., Computer programming., Computers., Artificial intelligence., Computer-aided engineering., Mathematical optimization., Electronic circuits., Circuits and Systems., Programming Techniques., Theory of Computation., Artificial Intelligence (incl. Robotics)., Computer-Aided Engineering (CAD, CAE) and Design., Optimization.,
Online Access:http://dx.doi.org/10.1007/978-1-4615-1035-2
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record_format koha
institution COLPOS
collection Koha
country México
countrycode MX
component Bibliográfico
access En linea
En linea
databasecode cat-colpos
tag biblioteca
region America del Norte
libraryname Departamento de documentación y biblioteca de COLPOS
language eng
topic Engineering.
Computer programming.
Computers.
Artificial intelligence.
Computer-aided engineering.
Mathematical optimization.
Electronic circuits.
Engineering.
Circuits and Systems.
Programming Techniques.
Theory of Computation.
Artificial Intelligence (incl. Robotics).
Computer-Aided Engineering (CAD, CAE) and Design.
Optimization.
Engineering.
Computer programming.
Computers.
Artificial intelligence.
Computer-aided engineering.
Mathematical optimization.
Electronic circuits.
Engineering.
Circuits and Systems.
Programming Techniques.
Theory of Computation.
Artificial Intelligence (incl. Robotics).
Computer-Aided Engineering (CAD, CAE) and Design.
Optimization.
spellingShingle Engineering.
Computer programming.
Computers.
Artificial intelligence.
Computer-aided engineering.
Mathematical optimization.
Electronic circuits.
Engineering.
Circuits and Systems.
Programming Techniques.
Theory of Computation.
Artificial Intelligence (incl. Robotics).
Computer-Aided Engineering (CAD, CAE) and Design.
Optimization.
Engineering.
Computer programming.
Computers.
Artificial intelligence.
Computer-aided engineering.
Mathematical optimization.
Electronic circuits.
Engineering.
Circuits and Systems.
Programming Techniques.
Theory of Computation.
Artificial Intelligence (incl. Robotics).
Computer-Aided Engineering (CAD, CAE) and Design.
Optimization.
Drechsler, Rolf. editor.
Drechsler, Nicole. editor.
SpringerLink (Online service)
Evolutionary Algorithms for Embedded System Design [electronic resource] /
description Evolutionary Algorithms for Embedded System Design describes how Evolutionary Algorithm (EA) concepts can be applied to circuit and system design - an area where time-to-market demands are critical. EAs create an interesting alternative to other approaches since they can be scaled with the problem size and can be easily run on parallel computer systems. This book presents several successful EA techniques and shows how they can be applied at different levels of the design process. Starting on a high-level abstraction, where software components are dominant, several optimization steps are demonstrated, including DSP code optimization and test generation. Throughout the book, EAs are tested on real-world applications and on large problem instances. For each application the main criteria for the successful application in the corresponding domain are discussed. In addition, contributions from leading international researchers provide the reader with a variety of perspectives, including a special focus on the combination of EAs with problem specific heuristics. Evolutionary Algorithms for Embedded System Design is an excellent reference for both practitioners working in the area of circuit and system design and for researchers in the field of evolutionary concepts.
format Texto
topic_facet Engineering.
Computer programming.
Computers.
Artificial intelligence.
Computer-aided engineering.
Mathematical optimization.
Electronic circuits.
Engineering.
Circuits and Systems.
Programming Techniques.
Theory of Computation.
Artificial Intelligence (incl. Robotics).
Computer-Aided Engineering (CAD, CAE) and Design.
Optimization.
author Drechsler, Rolf. editor.
Drechsler, Nicole. editor.
SpringerLink (Online service)
author_facet Drechsler, Rolf. editor.
Drechsler, Nicole. editor.
SpringerLink (Online service)
author_sort Drechsler, Rolf. editor.
title Evolutionary Algorithms for Embedded System Design [electronic resource] /
title_short Evolutionary Algorithms for Embedded System Design [electronic resource] /
title_full Evolutionary Algorithms for Embedded System Design [electronic resource] /
title_fullStr Evolutionary Algorithms for Embedded System Design [electronic resource] /
title_full_unstemmed Evolutionary Algorithms for Embedded System Design [electronic resource] /
title_sort evolutionary algorithms for embedded system design [electronic resource] /
publisher Boston, MA : Springer US : Imprint: Springer,
publishDate 2003
url http://dx.doi.org/10.1007/978-1-4615-1035-2
work_keys_str_mv AT drechslerrolfeditor evolutionaryalgorithmsforembeddedsystemdesignelectronicresource
AT drechslernicoleeditor evolutionaryalgorithmsforembeddedsystemdesignelectronicresource
AT springerlinkonlineservice evolutionaryalgorithmsforembeddedsystemdesignelectronicresource
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spelling KOHA-OAI-TEST:2068322018-07-30T23:36:38ZEvolutionary Algorithms for Embedded System Design [electronic resource] / Drechsler, Rolf. editor. Drechsler, Nicole. editor. SpringerLink (Online service) textBoston, MA : Springer US : Imprint: Springer,2003.engEvolutionary Algorithms for Embedded System Design describes how Evolutionary Algorithm (EA) concepts can be applied to circuit and system design - an area where time-to-market demands are critical. EAs create an interesting alternative to other approaches since they can be scaled with the problem size and can be easily run on parallel computer systems. This book presents several successful EA techniques and shows how they can be applied at different levels of the design process. Starting on a high-level abstraction, where software components are dominant, several optimization steps are demonstrated, including DSP code optimization and test generation. Throughout the book, EAs are tested on real-world applications and on large problem instances. For each application the main criteria for the successful application in the corresponding domain are discussed. In addition, contributions from leading international researchers provide the reader with a variety of perspectives, including a special focus on the combination of EAs with problem specific heuristics. Evolutionary Algorithms for Embedded System Design is an excellent reference for both practitioners working in the area of circuit and system design and for researchers in the field of evolutionary concepts.1 Evolutionary Testing of Embedded Systems -- 1. Introduction -- 2. Test Methods -- 3. Evolutionary Testing -- 4. Evolutionary Testing of Non-Functional Properties -- 5. Evolutionary Testing of Functional Behavior -- 6. Conclusion, Future Work -- 2 Genetic Algorithm Based DSP Code Optimization -- 1. Compilers for Digital Signal Processors -- 2. Address Generation in DSPs -- 3. Offset Assignment Problem -- 4. Genetic Algorithm Formulation -- 5. Experimental Results -- 6. Conclusions -- 3 Hierarchical Synthesis of Embedded Systems -- 1. Introduction -- 2. A Model for Embedded System Synthesis -- 3. System Synthesis -- 4. System Synthesis Using Evolutionary Algorithms -- 5. Hierarchical Design Space Exploration -- 6. Case Study -- 7. Conclusions -- 4 Functional Test Generation -- 1. Introduction -- 2. Functional Test Generation Algorithms -- 3. Proposed Hybrid Approach -- 4. Experimental Results -- 5. Concluding Remarks -- 5 Built-In Self Test of Sequential Circuits -- 1. Introduction -- 2. Cellular Automata -- 3. Test Architecture -- 4. The Selfish Gene Algorithm -- 5. Selfish Gene for CA-CSTP -- 6. Experimental Results -- 7. Conclusions.Evolutionary Algorithms for Embedded System Design describes how Evolutionary Algorithm (EA) concepts can be applied to circuit and system design - an area where time-to-market demands are critical. EAs create an interesting alternative to other approaches since they can be scaled with the problem size and can be easily run on parallel computer systems. This book presents several successful EA techniques and shows how they can be applied at different levels of the design process. Starting on a high-level abstraction, where software components are dominant, several optimization steps are demonstrated, including DSP code optimization and test generation. Throughout the book, EAs are tested on real-world applications and on large problem instances. For each application the main criteria for the successful application in the corresponding domain are discussed. In addition, contributions from leading international researchers provide the reader with a variety of perspectives, including a special focus on the combination of EAs with problem specific heuristics. Evolutionary Algorithms for Embedded System Design is an excellent reference for both practitioners working in the area of circuit and system design and for researchers in the field of evolutionary concepts.Engineering.Computer programming.Computers.Artificial intelligence.Computer-aided engineering.Mathematical optimization.Electronic circuits.Engineering.Circuits and Systems.Programming Techniques.Theory of Computation.Artificial Intelligence (incl. Robotics).Computer-Aided Engineering (CAD, CAE) and Design.Optimization.Springer eBookshttp://dx.doi.org/10.1007/978-1-4615-1035-2URN:ISBN:9781461510352