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Evolutionary Algorithms for Embedded System Design


Evolutionary Algorithms for Embedded System Design

edited by
Rolf Drechsler
Nicole Drechsler

Kluwer Academic Publishers
ISBN 1-4020-7276-7

Ordering:
Evolutionary Algorithms for Embedded System Design
can be ordered from publisher: Amazon.com

Book Summary:
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 practitioners working in the area of circuit and system design and for researchers in the field of evolutionary concepts.

Edited by:
Prof. Dr. Rolf Drechsler Rolf Drechsler received his diploma and Dr. phil. nat. degree in computer science from the J.W. Goethe-University in Frankfurt am Main, Germany, in 1992 and 1995, respectively. He was with the Institute of Computer Science at the Albert-Ludwigs-University of Freiburg im Breisgau, Germany from 1995 to 2000. He joint the Corporate Technology Department of Siemens AG, Munich in 2000, where he worked as a Senior Engineer in the formal verification group. Since October 2001 he is with the University of Bremen, Germany, where he is now a full professor for computer architecture. He published five books at Kluwer Academic Publishers. His research interests include verification, logic synthesis, and evolutionary algorithms.

Prof. Dr. Rolf Drechsler Nicole Drechsler received her diploma in Computer Science from the J.W. Goethe-University in Frankfurt am Main, Germany, in 1995. She worked as a research assistant at the Institute of Computer Science at the Albert-Ludwigs-University of Freiburg im Breisgau, Germany, from 1995 to 2000 and received Dr. rer. nat. degree in 2000. Since March 2002 she is employed at the University of Bremen, Germany, and her research interests include evolutionary algorithms in VLSI design and multi-objective optimization.

Fulvio Corno
Fabrizio Ferrandi
Alessandro Fin
Franco Fummi
Christian Haubelt
Rainer Leupers
Sanaz Mostaghim
Donatella Sciuto
Frank Slomka
Matteo Sonza Reorda
Giovanni Squillero
Jürgen Teich
Ambrish Tyagi
Joachim Wegener


Table of Contents:
  • Preface
  • Contributing Authors
  • Foreword
    by David E. Goldberg, Consulting Editor
  • Introduction
    by Rolf Drechsler and Nicole Drechsler
  • Evolutionary Testing of Embedded Systems
    by Joachim Wegener
  • Genetic Algorithm Based DSP Code Optimization
    by Rainer Leupers
  • Hierarchical Synthesis of Embedded Systems
    by Christian Haubelt, Sanaz Mostaghim, Frank Slomka, Jürgen Teich and Ambrish Tyagi
  • Functional Test Generation
    by Fabrizio Ferrandi, Donatella Scutio, Alessandro Fin and Franco Fummi
  • Built-In Self Test of Sequential Circuits
    by Fulvio Corno, Matteo Sonza Reorda and Giovanni Squillero

Other Volumes in the Kluwer Series on Genetic Algorithms and Evolutionary Computation (GENA):


Volume 1 | Efficient and Accurate Parallel Genetic Algorithms by Erick Cantú-Paz
Volume 2 | Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation by Pedro Larrañaga, José A. Lozano
Volume 3 | Evolutionary Optimization in Dynamic Environments by Jürgen Branke
Volume 4 | Anticipatory Learning Classifier Systems by Martin V. Butz
Volume 5 | Evolutionary Algorithms for Solving Multi-Objective Problems by Carlos A. Coello Coello, David A. Van Veldhuizen, Gary B. Lamont
Volume 6 | OmeGA: A Competent Genetic Algorithm for Solving Permutation and Scheduling Problems by Dimitri Knjazew
Volume 7 | The Design of Innovation by David E. Goldberg
Volume 8 | Noisy Optimization with Evolution Strategies by Dirk V. Arnold
Volume 9 | Classical and Evolutionary Algorithms in the Optimization of Optical Systems by Darko Vasiljevic




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