Title :
Unsupervised classification using associative memory
Author :
Sayeh, M.R. ; Li, B.
Author_Institution :
Dept. of Electr. & Comput. Eng., Southern Illinois Univ., Carbondale, IL, USA
Abstract :
In this paper, we present unsupervised classification using the Lyapunov Associative Memory (LYAM) system. This associative memory encodes the classification results as its equilibrium states. The system is modeled with only a set of nonlinear ordinary differential equations. An example is given for signal sorting application.
Keywords :
Lyapunov methods; content-addressable storage; nonlinear differential equations; pattern classification; LYAM; Lyapunov Associative Memory; classification results; equilibrium states; nonlinear ordinary differential equations; signal sorting application; unsupervised classification; Artificial neural networks; Associative memory; Differential equations; Earth; Encoding; Image segmentation; Neural networks; Nonlinear dynamical systems; Pattern clustering; Sorting;
Conference_Titel :
Circuits and Systems, 2002. MWSCAS-2002. The 2002 45th Midwest Symposium on
Print_ISBN :
0-7803-7523-8
DOI :
10.1109/MWSCAS.2002.1187246
