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We present a multichip, mixed-signal VLSI system for spike-based vision processing. The system consists of an 80 x 60 pixel neuromorphic retina and a 4800 neuron silicon cortex with 4,194,304 synapses. Its functionality is illustrated with experimental data on multiple components of an attention-based hierarchical model of cortical object recognition, including feature coding, salience detection, and foveation. This model exploits arbitrary and reconfigurable connectivity between cells in the multichip architecture, achieved by asynchronously routing neural spike events within and between chips according to a memory-based look-up table. Synaptic parameters, including conductance and reversal potential, are also stored in memory and are used to dynamically configure synapse circuits within the silicon neurons.

Covert, low-power and low-bandwidth sensor networks for intelligent surveillance require imaging front-ends that make rudimentary decisions to perform or facilitate data compression. Typically, this front-end is composed of a standard Active Pixel Sensor (APS), an ADC and additional digital logic for image processing and communication control. As is expected, these systems are large (unless integrated) with considerable power budgets. To circumvent these problems, a CMOS imager that integrates circuits for basic decision-making and image compression on the focal plane is described. The chip is used as a low-power vision sensor and wake-up detector for these ad hoc networks.

Index Terms-CMOS image sensor, computation-on-readout (COR), delta-difference sampling (DDS), pixel-level analog-to-digital conversion (ADC), temporal difference imager.

We present an architecture for processing spike-based sensory information in real-time. The system is based on a re-configurable silicon array of general-purpose integrate-and-fire neurons (as opposed to application-specific circuits), which can emulate arbitrary cortical networks. A combined retinal/cortical network has been designed and tested with a neuromorphic silicon retina. Neural activity is communicated between chips at rates of up to 1,000,000 spikes/sec with a bit-parallel Address-Event Representation protocol. This work represents the first step in constructing an autonomous, continuous-time, biologically-plausible hierarchical model of visual information processing using large-scale arrays of identical silicon neurons.

An integrated array of 2,400 spiking silicon neurons, with reconfigurable synaptic connectivity and adjustable neural spike-based dynamics, is presented. At the system level, the chip serves as an address-event transceiver, with incoming and outgoing spikes communicated over an asynchronous event-driven bus. Internally, every cell implements a spiking neuron that models general principles of synaptic operation as observed in biological membranes. Synaptic conductance and synaptic reversal potential can be dynamically modulated for each event. The implementation employs mixed-signal charge-based circuits to facilitate digital control of system parameters and minimize variability due to transistor mismatch. In addition to describing the structure of the silicon neurons, we present experimental data characterizing the operation of the 3mm × 3mm chip fabricated in 0.5µm CMOS technology.

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WORD ABSTRACTHerein we report on our contrast assessment and the development, sensing and control of the Vacuum Nuller Testbed to realize a Visible Nulling Coronagraphy (VNC) for exoplanet detection and characterization. The VNC is one of the few approaches that works with filled, segmented and sparse or diluted-aperture telescope systems. It thus spans a range of potential future NASA telescopes and could be flown as a separate instrument on such a future mission. NASA/Goddard Space Flight Center has an established effort to develop VNC technologies, and an incremental sequence of testbeds to advance this approach and its critical technologies. ABSTRACTHerein we report on our contrast assessment and the development, sensing and control of the Vacuum Nuller Testbed to realize a Visible Nulling Coronagraphy (VNC) for exoplanet detection and characterization. Tbe VNC is one of the few approaches that works with filled, segmented and sparse or diluted-aperture telescope systems. It thus spans a range of potential future NASA telescopes and could be flown as a separate instrument on such a future mission. NASA/Goddard Space Flight Center has an established effort to develop VNC technologies, and an incremental sequence of testbeds to advance this approach and its critical technologies. We discuss the development of the vacuum Visible Nulling Coronagraph testbed (VNT). The VNT is an ultra-stable vibration isolated testbed that operates under closed-loop control within a vacuum chamber. It will be used to achieve an incremental sequence of three visible-light nulling milestones with sequentially higher contrasts of 10', 10" and ideally 10 10 at an inner working angle of 2*AID. The VNT is based on a modified Mach-Zehnder nulling interferometer, with a "W" configuration to accommodate a hex-packed MEMS based deformable mirror, a coherent fiber bundle and achromatic phase shifters. We discuss the laboratory results, optical configruation, critical technologies !II1d the null sensing and control approach.