Iterative weighted finite transductions
Weighted finite transducers (WFT) and their application to image processing are investigated. It is shown that probabilistic mutually recursive function systems (PMRFS) can be simulated by iterative weighted finite transductions. It is conjectured that iterative WFT are stronger than PMRFS and examples of WFT that support this conjecture are given. Examples of iterative WFT, which compute mathematical functions given by a Taylor series with ``regular'' coefficients which cannot be computed by WFA, are given. An implementation of an efficient image manipulation system based on WFT is discussed. The system includes efficient algorithms for an application of a WFT transformation to an image in either pixel or WFA representation and for composition of WFT.
probabilistic mutually recursive function systems
scientific article; zbMATH DE number 818362