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Macromodelling for analog design and robustness boosting in bio-inspired computing models

By J. Cuadri, G. Liñán-Cembrano, Elisenda Roca and Ángel Rodríguez-Vázquez

Abstract

Setting specifications for the electronic implementation of biological neural-network-like vision systems on-chip is not straightforward, neither it is to simulate the resulting circuit. The structure of these systems leads to a netlist of more than 100.000 nodes for a small array of 100×150 pixels. Moreover, introducing an optical input in the low level simulation is nowadays not feasible with standard electrical simulation environments. Given that, to accomplish the task of integrating those systems in silicon to build compact, low power consuming, and reliable systems, a previous step in the standard analog electronic design flux should be introduced. Here a methodology to make the translation from the biological model to circuit-level specifications for electronic design is proposed. The purpose is to include non ideal effects as mismatching, noise, leakages, supply degradation, feedthrough, and temperature of operation in a high level description of the implementation, in order to accomplish behavioural simulations that require less computational effort and resources. A particular case study is presented, the analog electronic implementation of the locust's Lobula Giant Movement Detector (LGMD), a neural structure that fires a collision alarm based on visual information. The final goal is a collision threat detection vision system on-chip for automotive applications.This paper is partially funded by the European Project IST-2001-38097 (LOCUST), and TIC2003 - 09817-C02-01(VISTA). Mr. Cuadri’s work is funded by an F.P.U. grant from the Spanish Ministry of Education and Science.Peer Reviewe

Publisher: 'SPIE-Intl Soc Optical Eng'
Year: 2013
DOI identifier: 10.1117/12.608830
OAI identifier: oai:digital.csic.es:10261/85697
Provided by: Digital.CSIC
Journal:

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