FIFTHTM: A Stack Based GP Language for Vector Processing

  • Kenneth Holladay
  • Kay Robbins
  • Jeffery von Ronne
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4445)

Abstract

FIFTHTM, a new stack-based genetic programming language, efficiently expresses solutions to a large class of feature recognition problems. This problem class includes mining time-series data, classification of multivariate data, image segmentation, and digital signal processing (DSP). FIFTH is based on FORTH principles. Key features of FIFTH are a single data stack for all data types and support for vectors and matrices as single stack elements. We demonstrate that the language characteristics allow simple and elegant representation of signal processing algorithms while maintaining the rules necessary to automatically evolve stack correct and control flow correct programs. FIFTH supports all essential program architecture constructs such as automatically defined functions, loops, branches, and variable storage. An XML configuration file provides easy selection from a rich set of operators, including domain specific functions such as the Fourier transform (FFT). The fully-distributed FIFTH environment (GPE5) uses CORBA for its underlying process communication.

Keywords

Genetic Programming vectors linear GP GP environment 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Kenneth Holladay
    • 1
  • Kay Robbins
    • 2
  • Jeffery von Ronne
    • 2
  1. 1.Southwest Research Institute, San Antonio, Texas 
  2. 2.University of Texas at San Antonio, San Antonio, Texas 

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