Title :
A Low-Power Current Mode Fuzzy-ART Cell
Author :
Serrano-Gotarredona, T. ; Linares-Barranco, B.
Author_Institution :
Inst. de Microelectron. de Sevilla
Abstract :
This paper presents a very large scale integration (VLSI) implementation of a low-power current-mode fuzzy-adaptive resonance theory (ART) cell. The cell is based on a compact new current source multibit memory cell with online learning capability. A small prototype of the designed cell and its peripheral block has been fabricated in the AustriaMicroSystems (AMS)-0.35-mum technology. The cell occupies a total area of 44 times 34 mum2 and consumes a maximum current of 22 nA
Keywords :
ART neural nets; VLSI; fuzzy neural nets; learning (artificial intelligence); hardware implementations; low-power current-mode fuzzy-adaptive resonance theory; source multibit memory cell; very large scale integration; Application software; Clustering algorithms; Control systems; Hardware; Neural networks; Pattern recognition; Prototypes; Resonance; Subspace constraints; Very large scale integration; Adaptive resonance theory (ART); hardware implementations; low power; Algorithms; Electric Power Supplies; Equipment Design; Equipment Failure Analysis; Fuzzy Logic; Information Storage and Retrieval; Miniaturization; Neural Networks (Computer); Pattern Recognition, Automated; Semiconductors; Signal Processing, Computer-Assisted;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2006.883725
