Multilinear algebraic boolean modelling with tensor decompositions techniques

The paper first shows that Kruskal tensors with matrix factors derived from orthogonal ternary vector lists define multivariable Boolean functions. These tensors make it possible to derive efficient algorithms for the generation of equivalent Zhegalkin polynomials, which are secondly used for identification of algebraic Boolean models, e.g. for gene expression dynamics. © 2011 IFAC.Unknow