Theoretical Foundation Toshiba Laboratory Theoretical Foundation Toshiba Laboratory Objectives Integration of Symbols and patterns is our study. Analyzing the relation between logics and function space, and building the theories and algorithms for pattern inference are our research topics. The detailed relationships between the multilinear function space and the above logics are studied.
Patterns are functions and the functions can be approximated by neural networks.
Therefore, pattern reasonings can be realized by logical reasonings of neural networks. The reasonings of neural networks by several nonclassical logics such as an intermediate logic LC, BCK logics and linear logics are studied. So, the mechanisms that make neural networks simple are needed to reduce processing time and to make inference precision high because of redundancy of neural networks. We are trying to develop the algorithm which reduces the redundancy using evolutionary computations and statistics. A tool for neural network simulation and structure analysis and is under developing now.