Title :
The Configurable Digital Cellular Neural - Hopfield Network
Author :
Zeffer, Tamas ; Hidvegi, Timot
Author_Institution :
Fac. of Inf. Technol., Peter Pazmany Catholic Univ., Budapest
Abstract :
A configurable artificial neuron network that is capable of establishing both the emulated digital cellular neural network (CNN) and the Hopfield network is described. The configurable neural network is designed with the method of modularity where each module is a three weighted input neuron. The network can be optionally large limited only by the gate number available on a chip. Also, the network is reconfigurable during operation
Keywords :
Hopfield neural nets; cellular neural nets; neural chips; Hopfield network; configurable artificial neuron network; emulated digital cellular neural network; gate number; modularity method; neural chip; Arithmetic; Artificial neural networks; Cellular networks; Cellular neural networks; Equations; Hopfield neural networks; Information technology; Neural networks; Neurons; Strontium;
Conference_Titel :
Intelligent Engineering Systems, 2006. INES '06. Proceedings. International Conference on
Conference_Location :
London
Print_ISBN :
0-7803-9708-8
DOI :
10.1109/INES.2006.1689361
