Microelectronic Implementations of Connectionist Neural Networks

Part of Neural Information Processing Systems (NIPS 1987)

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Stuart Mackie, Hans Graf, Daniel Schwartz, John Denker


In this paper we discuss why special purpose chips are needed for useful implementations of connectionist neural networks in such applications as pattern recognition and classification. Three chip designs are described: a hybrid digital/analog programmable connection matrix, an analog connection matrix with adjustable connection strengths, and a digital pipe lined best-match chip. The common feature of the designs is the distribution of arithmetic processing power amongst the data storage to minimize data movement.