Title :
An asynchronous weightless neural network for discrete relaxation problems
Author :
Alnuweiri, H.M. ; Gange, D.
Author_Institution :
Centre for Integrated Comput. Res., British Columbia Univ., Vancouver, BC, Canada
fDate :
2/1/1998 12:00:00 AM
Abstract :
This paper proposes a weightless neural network for solving discrete relaxation problems. The network implements a parallel version of a new efficient sequential algorithm for the consistent labeling problem. The proposed neural network consists of a feedback interconnection of three layers of very simple neurons that operate in an asynchronous fashion. Because of the simple structure of the neurons, the neural network can be implemented using highly regular AND/OR VLSI arrays. The asynchronous operation eliminates the need for using clocks or placing registers between the different layers and along the feedback paths of the network, thus resulting in very fast convergence time
Keywords :
CMOS digital integrated circuits; VLSI; asynchronous circuits; circuit feedback; convergence of numerical methods; neural chips; neural net architecture; parallel algorithms; parallel architectures; relaxation theory; asynchronous weightless neural network; consistent labeling problem; fast convergence time; feedback interconnection; highly regular AND/OR VLSI arrays; iscrete relaxation problems; Clocks; Convergence; Integrated circuit interconnections; Labeling; Logic gates; Neural networks; Neurofeedback; Neurons; Registers; Very large scale integration;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on