A Real Time Clustering CMOS Neural Engine

We describe an analog VLSI implementation of the ARTI algorithm (Carpenter, 1987). A prototype chip has been fabricated in a standard low cost 1.5~m double-metal single-poly CMOS process. It has a die area of lcm2 and is mounted in a 12O-pins PGA package. The chip realizes a modified version of the original ARTI architecture. Such modification has been shown to preserve all computational properties of the original algorithm (Serrano, 1994a), while being more appropriate for VLSI realizations. The chip implements an ARTI network with 100 F 1 nodes and 18 F2 nodes. It can therefore cluster 100 binary pixels input patterns into up to 18 different categories. Modular expansibility of the system is possible by assembling an NxM array of chips without any extra interfacing circuitry, resulting in an F 1 layer with l00xN nodes, and an F2 layer with 18xM nodes. Pattern classification is performed in less than 1.8~s, which means an equivalent computing power of 2.2x109 connections and connection-updates per second. Although internally the chip is analog in nature, it interfaces to the outside world through digital signals, thus having a true asynchrounous digital behavior. Experimental chip test results are available, which have been obtained through test equipments for digital chips.