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A GENETIC ALGORITHM TECHNIQUE FOR APPROXIMATING FUNCTIONS OF MULTIPLE INDEPENDENT VARIABLES

GURUMURTHY, ARAVIND

Abstract Details

2003, MS, University of Cincinnati, Engineering : Electrical Engineering.
This thesis addresses approximation of functions of multiple independent variables. Engineers generally use look up tables, Taylor series or other series representations for interpolating data, with varying degrees of accuracy. In this research we consider another method. We extend a genetic algorithm technique for approximating functions of one variable with a set of polynomials, with integer coefficients, to functions of more than one variable. The goal is to minimize the sum of squared errors over a range of experimentally gathered or sampled data. This research is particularly applicable to semi-custom hardware designs and embedded programming applications.
Dr. Carla Purdy (Advisor)
132 p.

Recommended Citations

Citations

  • GURUMURTHY, A. (2003). A GENETIC ALGORITHM TECHNIQUE FOR APPROXIMATING FUNCTIONS OF MULTIPLE INDEPENDENT VARIABLES [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1065654138

    APA Style (7th edition)

  • GURUMURTHY, ARAVIND. A GENETIC ALGORITHM TECHNIQUE FOR APPROXIMATING FUNCTIONS OF MULTIPLE INDEPENDENT VARIABLES. 2003. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1065654138.

    MLA Style (8th edition)

  • GURUMURTHY, ARAVIND. "A GENETIC ALGORITHM TECHNIQUE FOR APPROXIMATING FUNCTIONS OF MULTIPLE INDEPENDENT VARIABLES." Master's thesis, University of Cincinnati, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1065654138

    Chicago Manual of Style (17th edition)