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This paper describes the electronic implementation of a four-layer cellular neural network architecture implementing two components of a functional model of neurons in the visual cortex: linear orientation selective filtering and half wave rectification. Separate ON and OFF layers represent the positive and negative outputs of two-phase quadrature Gabor-type filters, whose orientation and spatial-frequency tunings are electronically adjustable. To enable the construction of a multichip network to extract different orientations in parallel, the chip includes an address event representation (AER) transceiver that accepts and produces two-dimensional images that are rate encoded as spike trains. It also includes routing circuitry that facilitates point-to-point signal fan in and fan out. We present measured results from a 32 x 64 pixel prototype, which was fabricated in the TSMC0.25-μm process on a 3.84 by 2.54 mm die. Quiescent power dissipation is 3 mW and is determined primarily by the spike activity on the AER bus. Settling times are on the order of a few milliseconds. In comparison with a two-layer network implementing the same filters, this network results in a more symmetric circuit design with lower quiescent power dissipation, albeit at the expense of twice as many transistors.
address event representation (AER), analog circuits, asynchronous logic, Gabor filter, image processing, neuromorphic engineering, nonlinear circuits, visual cortex
Date Posted: 10 November 2004
This document has been peer reviewed.