Publication Date


Document Type


First Advisor

Bobis, James P.

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Electrical Engineering


Genetic algorithms; Electric circuits; linear


Recent advances in computer capabilities have eliminated much of the trial and error evaluation of traditional engineering design. Currently, computers are utilized to electronically build and test possible solutions to the problem at hand. This capability is a major advancement in engineering problem solving, allowing evaluation of several potential solutions quickly and inexpensively. The next logical step is to allow the computer to have an additional role. To this end, artificial intelligence and expert systems have, in a limited manner, transitioned from the universities to the industrial community. An emerging tool for computer aided design and computer aided engineering (CAD/CAE) is the genetic algorithm. This paper discusses an application of a genetic algorithm to linearization circuit design. From this application, support is given for improved understanding of genetic algorithm application theory. Specifically, the relationship between the properties of a genetic algorithm and circuit parameter sensitivity is explored. This study shows linearization circuits may be dramatically improved with the aid of a genetic algorithm. Additionally, there appears to be a correlation between the convergence of parameters during a genetic algorithm run and the relative sensitivity of the circuit to variation of the parameters.


Includes bibliographical references (pages [56]-58)


ix, 78 pages




Northern Illinois University

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