Acceleration Technique for Neuro Symbolic Integration

This paper presents an improved technique for accelerating the process of doing logic programming in discrete Hopfield neural network by integrating fuzzy logic and modifying activation function. Generally Hopfield networks are suitable for solving combinatorial optimization problems and pattern recognition problems. However Hopfield neural networks also face some limitations; one of the major limitation is the solutions are local minima rather than global minima. Hereby, we introduce an improved technique by integrating Hopfield network, modifying activation function and fuzzy logic technique to have better energy relaxation and global solutions. Computer simulations are carried out to verify and validate the proposed approach.