Teresa Serrano-Gotarredona

PubMed2006

A low-power current mode fuzzy-ART cell.

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-microm technology. The cell occupies a total area of 44 x 34 microm2 and consumes a maximum current of 22 nA.

Algorithms↗

PubMed1996

A Modified ART 1 Algorithm more Suitable for VLSI Implementations.

This paper presents a modification to the original ART 1 algorithm ([Carpenter and Grossberg, 1987a], A massively parallel architecture for a self-organizing neural pattern recognition machine, Computer Vision, Graphics, and Image Processing, 37, 54-115) that is conceptually similar, can be implemented in hardware with less sophisticated building blocks, and maintains the computational capabilities of the originally proposed algorithm. This modified ART 1 algorithm (which we will call here ART 1(m)) is the result of hardware motivated simplifications investigated during the design of an actual ART 1 chip [Serrano-Gotarredona et al., 1994, Proc. 1994 IEEE Int. Conf. Neural Networks (Vol. 3, pp. 1912-1916); [Serrano-Gotarredona and Linares-Barranco, 1996], IEEE Trans. VLSI Systems, (in press)]. The purpose of this paper is simply to justify theoretically that the modified algorithm preserves the computational properties of the original one and to study the difference in behavior between the two approaches. Copyright 1996 Elsevier Science Ltd.

Journal Article↗