Patent ID: 6353816
Filing Date: 2002-03-05
Classification: G06N

Abstract:
A neural network analysis method comprising:inputting each intermediate and output element of a trained neural network to be analyzed as data represented by a multilinear function, the neural network having been trained by learning data in a given domain; approximating each intermediate and output element with a Boolean function approximation; synthesizing the Boolean function approximation of each intermediate and output element into a synthesized Boolean function; and outputting data, including the synthesized Boolean function, which is indicative of a predictive accuracy of the trained neural network, as an analysis result; wherein approximating each intermediate and output element with a Boolean function approximation further comprises, generating terms of a Boolean function for each intermediate and output element, and linking the terms using a logical sum to obtain a Boolean function approximation of each intermediate and output element, and said generating terms of a Boolean function for each intermediate and output element repeats a process comprising selecting a term that is made from a variable representing each intermediate and output element, limiting the learning data in the given domain to data within a limited subdomain corresponding to the term that is made from a variable, and making a judgment as to whether the term that is made from a variable exists in the Boolean function approximation based on data within the limited subdomain.