A general purpose analog neural computer and a silicon retina for real time target acquisition, recognition and tracking

Abstract

The application of a general purpose analog neural computer (GPANC) and a smart silicon retina to target recognition, acquisition and tracking is discussed. The GPANC is designed as a general purpose tool for the implementation of real time neural based solutions to real world problems. It is composed of modules which mimic biological neurons, synapses and axon/dendrites. The modules are fully programmable and are arranged in macro cells to facilitate gross expansion of the computer. The presented version is composed of 10/sup 3/ neurons, 10/sup 5/ synapses, 10/sup 4/ synaptic time constants and 6 /spl times/ 10/sup 5/ interconnection switches. Its computation rate is 10/sup 11/ CPS or it can solve 10/sup 3/ nonlinear functions of 10/sup 4/ coupled first order differential equations in real time. Except for a digital host for programming the GPANC, it operates in full continuous time analog mode and offers temporal computational capabilities. The silicon retina is designed for autonomous target acquisition and tracking and serves as the front-end to the GPANS. It features a space variant layout of photoreceptors, logarithmic compress of incident light intensity, edge detection, motion detection in the fovea and temporal modulation detection in the periphery. All computation circuits are implemented at the focal plane. The peripheral pixels report the location of arriving targets which are then foveated. The fovea is composed of an array of densely pack photoreceptors where full 2D velocity, spanning three orders of magnitude, is computed. Using a closed loop velocity error correction technique, the target's velocity relative to the retina is zeroed. Therefore, using the periphery of retina for acquiring a target, the GPANC for target recognition and system control, and the fovea of retina for tracking, a fully autonomous targeting system can be realized.