Solving algebraic and geometrical problems using neural networks

Abstract

Neural networks have been used over many years to help solve a large range of problems in pattern recognition, control and general signal processing. In this sense “neural computing” has generally been restricted to these types of domains. In contrast, here we investigate how neural networks can be adapted to actually solve numerical problems in algebra and geometry by modelling connections and transducer functions.