TY - JOUR

T1 - Vector space formulation of probabilistic finite state automata

AU - Wen, Yicheng

AU - Ray, Asok

N1 - Funding Information:
✩ This work has been supported in part by the US Office of Naval Research under Grant No. N00014-09-1-0688, and by the US Army Research Laboratory and the US Army Research Office under Grant No. W911NF-07-1-0376. * Corresponding author. E-mail addresses: ywen2000@gmail.com (Y. Wen), axr2@psu.edu (A. Ray). 1 Currently with General Electric, Louisville, KY, United States.

PY - 2012/7

Y1 - 2012/7

N2 - This paper develops a vector space model of a class of probabilistic finite state automata (PFSA) that are constructed from finite-length symbol sequences. The vector space is constructed over the real field, where the algebraic operations of vector addition and the associated scalar multiplication operations are defined on a probability measure space, and implications of these algebraic operations are interpreted. The zero element of this vector space is semantically equivalent to a PFSA, referred to as symbolic white noise. A norm is introduced on the vector space of PFSA, which provides a measure of the information content. An application example is presented in the framework of pattern recognition for identification of robot motion in a laboratory environment.

AB - This paper develops a vector space model of a class of probabilistic finite state automata (PFSA) that are constructed from finite-length symbol sequences. The vector space is constructed over the real field, where the algebraic operations of vector addition and the associated scalar multiplication operations are defined on a probability measure space, and implications of these algebraic operations are interpreted. The zero element of this vector space is semantically equivalent to a PFSA, referred to as symbolic white noise. A norm is introduced on the vector space of PFSA, which provides a measure of the information content. An application example is presented in the framework of pattern recognition for identification of robot motion in a laboratory environment.

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U2 - 10.1016/j.jcss.2012.02.001

DO - 10.1016/j.jcss.2012.02.001

M3 - Article

AN - SCOPUS:84858437533

VL - 78

SP - 1127

EP - 1141

JO - Journal of Computer and System Sciences

JF - Journal of Computer and System Sciences

SN - 0022-0000

IS - 4

ER -