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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.
Content Level »Professional/practitioner
Keywords »Embedded Systems - System - algorithms - digital signal processor - evolutionary algorithm - genetic algorithms - heuristics - optimization
Preface. Contributing Authors.
Foreword; D.E. Goldberg.
Introduction; R. Drechsler, N. Drechsler.
1. Evolutionary Testing of Embedded Systems; J. Wegener.
2. Genetic Algorithm Based DSP Code Optimization; R. Leupers.
3. Hierarchical Synthesis of Embedded Systems; C. Haubelt, et al.
4. Functional Test Generation; F. Ferrandi, et al.
5. Built-in Self Test of Sequential Circuits; F. Corno, et al.