Distortion invariant pattern recognition is an interesting problem from the biological and technological point of view. However, it has not yet been solved by neural networks in satisfactory way. This paper investigates an associative neural network system to improve the recalling accuracy for distortion patterns. On a perception type of neural network with feedback, error back-propagation algorithm and energy function are used for a learning process and a recalling process, respectively. By using gradated patterns as learning and unknown patterns, it is shown that the recalling accuracy becomes higher than using original pattern themselves.
['Kazukuni Kobara', 'Taiho Kanaoka', 'Yoshihiko Hamamoto', 'Shingo Tomita', 'Koukichi Munechika']
Use of gradated patterns in an associative neural memory for invariant pattern recognition