PROBABILISTIC FINITE STATE SYSTEM IDENTIFICATION

Abstract

This paper explores the problem of finding behavioral models of finite state systems, given observed data of systems which are presumed to lie in this category.

Following an informal introduction, a formal definition of an identification problem is given along with the form that a solution to such a problem may be expected to lake.

The most general type of such problem involving finite state systems is described and several possible approaches to developing a solution to this general problem are discussed.

Several classes of more specialized classes of systems and their identification problems are developed. For these, a set of algorithms are described which may be used to solve them. The complexity of these algorithms is discussed.

INDEX TERMS:

• System identification
• finite state systems
• probabilistic systems.

Additional information

Notes on contributors

ROBERT GERARDY

Robert Gerardy was born on August 3, 1943. He received the B. S. degree in Physics from Washburn University in Topeka, Kansas in 1964. Following ten years in various governmental and industrial positions, he entered graduate school at the State University of New York at Binghamton, receiving the M. S. in 1975 and the Ph.D in 1981. Dr. Gerardy is currently assistant professor of Computer Science at Southern Illinois University at Edwardsville. Prior to that he was assistant professor of Computer Science at Montana Slate University