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Evolvable Hardware Using Genetic Programming

  • Nadia Nedjah
  • Luiza de Macedo Mourelle
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2690)

Abstract

In this paper, we propose a methodology based on genetic programming to automatically generate data-flow based specifications for hardware designs of combinational digital circuits. We aim at allowing automatic generation of balanced hardware specifications for a given input/output behaviour. It minimises space while maintaining reasonable response time.

Keywords

Input Signal Genetic Programming Propagation Delay Digital Circuit Combinational Circuit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Aho, A.V., Ravi, S., Ullman, J.D.: Compilers: principles, techniques and tools. Addison-Wesley, Reading (1986)Google Scholar
  2. 2.
    Coelho, A.A.C., Christiansen, A.D., Aguirre, A.H.: Towards Automated Evolutionary Design of Combinational Circuits. Comput. Electr. Eng. 27, 1–28 (2001)CrossRefGoogle Scholar
  3. 3.
    Ercegovac, M.D., Lang, T., Moreno, J.H.: Introduction to digital systems. John Wiley, Chichester (1999)Google Scholar
  4. 4.
    Koza, J.R.: Genetic Programming. MIT Press, Cambridge (1992)zbMATHGoogle Scholar
  5. 5.
    Miller, J.F., Job, D.: Principles in the evolutionary design of digital circuitsGoogle Scholar
  6. 6.
    Rhyne, V.T.: In: Kuo, F.F. (ed.) Fundamentals of digital systems design. Electrical Engineering Series. Prentice-Hall, Englewood Cliffs (1973)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Nadia Nedjah
    • 1
  • Luiza de Macedo Mourelle
    • 1
  1. 1.Department of Systems Engineering and Computation, Faculty of EngineeringState University of Rio de JaneiroRio de JaneiroBrazil

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