SYNERGETIC LEARNING FOR UNSUPERVISED TEXTURE CLASSIFICATION TASKS

Synergetic computers form a class of self-organized algorithms. Due to their close similarity to nonlinear self-organized systems in physics and chemistry they are potential candidates for a new sort of image p rocessing hardware. We will study the performance of an unsupervised s ynergetic learning algorithm with classification problems on both arti fical and real texture data and will show that unsupervised synergetic learning can be successfully used for unsupervised pattern classifica tion.