Evolutionary Algorithms for Embedded System Design edited by Rolf Drechsler, Nicole Drechsler.

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 s...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Drechsler, Rolf (Editor), Drechsler, Nicole (Editor)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 2003.
Edition:1st ed. 2003.
Series:Genetic Algorithms and Evolutionary Computation, 10
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 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.