Hypersonic, page-51

Neutron-Induced, Single-Event Effects on Neuromorphic Event-Based Vision Sensor: A First Step and Tools to Space Applications

Authors:
Seth Roffe; Himanshu Akolkar; Alan D. George; Bernabé Linares-Barranco; Ryad B. Benosman

Abstract:

This paper studies the suitability of neuromorphic event-based vision cameras for spaceflight and the effects of neutron radiation on their performance. Neuromorphic event-based vision cameras are novel sensors that implement asynchronous, clockless data acquisition, providing information about the change in illuminance $\ge 120dB$ with sub-millisecond temporal precision. These sensors have huge potential for space applications as they provide an extremely sparse representation of visual dynamics while removing redundant information, thereby conforming to low-resource requirements. An event-based sensor was irradiated under wide-spectrum neutrons at Los Alamos Neutron Science Center and its effects were classified. Radiation-induced damage of the sensor under wide-spectrum neutrons was tested, as was the radiative effect on the signal-to-noise ratio of the output at different angles of incidence from the beam source. We found that the sensor had very fast recovery during radiation, showing high correlation of noise event bursts with respect to source macro-pulses. No statistically significant differences were observed between the number of events induced at different angles of incidence but significant differences were found in the spatial structure of noise events at different angles. The results show that event-based cameras are capable of functioning in a space-like, radiative environment with a signal-to-noise ratio of 3.355. They also show that radiation-induced noise does not affect event-level computation. Finally, we introduce the Event-based Radiation-Induced Noise Simulation Environment (Event-RINSE), a simulation environment based on the noise-modelling we conducted and capable of injecting the effects of radiation-induced noise from the collected data to any stream of events in order to ensure that developed code can operate in a radiative environment. To the best of our knowledge, this is the first time such analysis of neutron-induced noise has been performed on a neuromorphic vision sensor, and this study shows the advantage of using such sensors for space applications.

https://hotcopper.com.au/threads/all-roads-lead-to-jast.5683524/

Bernabé Linares-Barranco:

Method, digital electronic circuit and system for unsupervised detection of repeating patterns in a series of events

Inventor

Jacob Martin

Amir Reza YOUSEFZADEH

Simon Thorpe

Timothée MASQUELIER

Bernabe LINARES-BARRANCO

Abstract

A method of performing unsupervised detection of repeating patterns in a series of events, includes a) Providing a plurality of neurons, each neuron being representative of W event types; b) Acquiring an input packet comprising N successive events of the series; c) Attributing to at least some neurons a potential value, representative of the number of common events between the input packet and the neuron; d) Modify the event types of neurons having a potential value exceeding a first threshold TL; and e) generating a first output signal for all neurons having a potential value exceeding a second threshold TF, and a second output signal, different from the first one, for all other neurons. A digital electronic circuit and system configured for carrying out such a method is also provided

https://www.asx.com.au/asxpdf/20170320/pdf/43gxg7g8c6xq25.pdf

Method, digital electronic circuit and system for unsupervised detection of repeating patterns in a series of events, European Patent Office EP17305186 Feb2017, Amirreza Yousefzadeh, Bernabe Linares-Barranco, Timothee Masquelier, Jacob Martin, Simon Thorpe, Exclusive Licensed to the Californian start-up BrainChip.