Spike-Based Analog-Digital Neuromorphic Information Processing System for Sensor Applications

Giovanny Sanchez*, Thomas Jacob Koickal, T. A. Athul Sripad, Luiz Carlos Gouveia, Alister Hamilton, Jordi Madrenas

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A spiking-neuron-based system that combines analog and digital multi-processor implementations for the bio-inspired processing of sensors is reported. This combination allows creating a powerful bio-inspired multiple-input sensor processing system for environment perception applications. The analog front-end encodes the input signal in a signed spike representation, which is further processed by means of a digital Spiking Neural Network (SNN) on a Single-Instruction Multiple-Data (SIMD) multiprocessor. The spike distribution for both systems is based on Address-Event Representation (AER) scheme, asynchronous for the Analog Pre-Processor (APP) and synchronous for the Digital Multi-Processor (DMP), synchronized by means of an AER transceiver. A proof-of-concept application of the system being able to process sensory information has been demonstrated. The system utilizes 30-neurons emulated by the DMP to process spike-encoded information provided by its analog counterpart, enabling the feature extraction of the input signal. The frequency detection capability of the system is experimentally reported.

Original languageEnglish
Title of host publication2013 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1624-1627
Number of pages4
ISBN (Print)978-1-4673-5760-9
Publication statusPublished - 2013
EventIEEE International Symposium on Circuits and Systems (ISCAS) - Beijing, Beijing, United Kingdom
Duration: 19 May 201323 May 2013

Publication series

NameIEEE International Symposium on Circuits and Systems
PublisherIEEE
ISSN (Print)0271-4302

Conference

ConferenceIEEE International Symposium on Circuits and Systems (ISCAS)
CountryUnited Kingdom
CityBeijing
Period19/05/1323/05/13

Keywords

  • NEURAL-NETWORKS

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