MANY-VALUED FUNCTION LEARNING METHOD

摘要

PURPOSE: To provide the many-valued function learning method based on function approximation for calculating a many-valued function expressing the input/ output relation of systems from input/output sampling data with learning due to the calculus of variation and for estimating an output value corresponding to unknown input data according to the result. ;CONSTITUTION: The input/output function of the system is learnt by expressing the conditions satisfied by input/output sampling data x→ and y→ with an equation using a tensor product, transforming the expression with new scolar value functions F₁, G₁, F₂, G₂ and H so that the expression can be made linear, solving the scolar value functions by using the calculus of variation as the minimizing problem of energy general functions defined by those scolar value functions, and finally performing inverse transform from the scolar value functions to many-valued functions.;COPYRIGHT: (C)1995,JPO