Bias Current Generators with Wide Dynamic Range

Mixed-signal or analog chips often require a wide range of biasing currents that are independent of process and supply voltage and that are proportional to absolute temperature. This paper describes CMOS circuits that we use to generate a set of fixed bias currents typically spanning six decades at room temperature down to a few times the transistor off-current. A bootstrapped current reference with a new startup and power-control mechanism generates a master current, which is successively divided by a current splitter to generate the desired reference currents. These references are nondestructively copied to form the chip's biases. Measurements of behavior, including temperature effects from 1.6 and 0.35 μ implementations, are presented and nonidealities are investigated. Temperature dependence of the transistor off-current is investigated because it determines the lower limit for generated currents. Readers are directed to a design kit that allows easy generation of the complete layout for a bias generator with a set of desired currents for scalable MOSIS CMOS processe

Adaptive Photoreceptor with Wide Dynamic Range

We describe a photoreceptor circuit that can be used in massively parallel analog VLSI silicon chips, in conjunction with other local circuits, to perform initial analog visual information processing. The receptor provides a continuous-time output that has low gain for static signals (including circuit mismatches), and high gain for transient signals that are centered around the adaptation point. The response is logarithmic, which makes the response to a fixed image contrast invariant to absolute light intensity. The 5-transistor receptor can be fabricated in an area of about 70 μm by 70 μm in a 2-μm single-poly CMOS technology. It has a dynamic range of 1-2 decades at a single adaptation level, and a total dynamic range of more than 6 decades. Several technical improvements in the circuit yield an additional 1-2 decades dynamic range over previous designs without sacrificing signal quality. The lower limit of the dynamic range, defined arbitrarily as the illuminance at which the bandwidth of the receptor is 60 Hz, is at approximately 1 lux, which is the border between rod and cone vision and also the limit of current consumer video cameras. The receptor uses an adaptive element that is resistant to excess minority carrier diffusion. The continuous and logarithmic transduction process makes the bandwidth scale with intensity. As a result, the total A.C. RMS receptor noise is constant, independent of intensity. The spectral density of the noise is within a factor of two of pure photon shot noise and varies inversely with intensity. The connection between shot and thermal noise in a system governed by Boltzman statistics is beautifully illustrated

AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems

A 5-layer neuromorphic vision processor whose components communicate spike events asychronously using the address-eventrepresentation (AER) is demonstrated. The system includes a retina chip, two convolution chips, a 2D winner-take-all chip, a delay line chip, a learning classifier chip, and a set of PCBs for computer interfacing and address space remappings. The components use a mixture of analog and digital computation and will learn to classify trajectories of a moving object. A complete experimental setup and measurements results are shown.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C0

Direction selective silicon retina that uses null inhibition

Biological retinas extract spatial and temporal features in an attempt to reduce the complexity of performing visual tasks. We have built and tested a silicon retina which encodes several useful temporal features found in vertebrate retinas. The cells in our silicon retina are selective to direction, highly sensitive to positive contrast changes around an ambient light level, and tuned to a particular velocity. Inhibitory connections in the null direction perform the direction selectivity we desire. This silicon retina is on a 4.6×6.8mm die and consists of a 47×41 array of photoreceptors.

Bias Current Generators with Wide Dynamic Range

This paper describes CMOS circuits that generate a wideranging set of fixed bias currents, spanning at least 6 decades down to picoamperes. A master current generated by a bootstrapped current reference is successively divided by a current splitter to generate the desired references. An unpublished startup circuit and a novel power control mechanism are described. Measurements from a 0.35u implementation are presented and nonidealities are investigated. Readers are directed to a design kit that makes it simple to generate the layout for a bias generator with a set of desired currents for scalable MOSIS CMOS processes

Time-derivative adaptive silicon photoreceptor array

We designed and tested a two-dimensional silicon receptor array constructed from pixels that temporally highpass filter the incident image. There are no surround interactions in the array; all pixels operate independently except for their correlation due to the input image. The high-pass output signal is computed by sampling the output of an adaptive, high-gain, logarithmic photoreceptor during the scanout of the array. After a pixel is sampled, the output of the pixel is reset to a fixed value. An interesting capacitive coupling mechanism results in a controllable high-pass filtering operation. The resulting array has very low offsets. The computation that the array performs may be useful for time-domain image processing, for example, motion computation. 1. TIME-DOMAIN IMAGE PROCESSING Real-time image processing is expensive. Much of the computational load involved in computing motion parallax, optical flow, and object tracking lies in the image preprocessing, before any sophisticated global vision algorithms are applied. Specialized parallel digital processors like the PIPE machine have been used to do real-time, time-domain, image processing. These machines are reprogrammable and flexible in their applications, and have been used to implement algorithms developed by the machine vision community, 2 and also to model biological visual function. 11 Since the