New Associative Memory System and Its Learning Convergence

A new high order Associative Memory System based on Newton forword interpolation formula (NFI AMS) used for implementing hign precision approximation to multi variable polynomial functions with arbitrarily given order is proposed.The learning algorithm of NFI AMS is designed.Moreover,it is proved that the NFI AMS learning always converges to a given multivariable continuous function with arbitrary accuracy under a wide condition.The AMS possesses the advantages over conventional CMAS type AMS less learning sample points,high precision of learning and much less required memory size,and also the advantages over multi layer BP neural networks in much less computational effort for training and fast convergence rate.The systems of NFI AMS has great potential in the application areas of intelligent control and signal processing,process modelling and pattern recognition.