6533b851fe1ef96bd12a9982

RESEARCH PRODUCT

Visual spike-based convolution processing with a Cellular Automata architecture

Anton CivitAlejandro Linares-barrancoGabriel JiménezJ. CerdaN. FerrandoM. Rivas-perez

subject

Very-large-scale integrationSignal processingTheoretical computer scienceArtificial neural networkComputer sciencebusiness.industrySensory systemCellular automatonConvolutionNeuromorphic engineeringAsynchronous communicationSpike (software development)businessComputer hardware

description

this paper presents a first approach for implementations which fuse the Address-Event-Representation (AER) processing with the Cellular Automata using FPGA and AER-tools. This new strategy applies spike-based convolution filters inspired by Cellular Automata for AER vision processing. Spike-based systems are neuro-inspired circuits implementations traditionally used for sensory systems or sensor signal processing. AER is a neuromorphic communication protocol for transferring asynchronous events between VLSI spike-based chips. These neuro-inspired implementations allow developing complex, multilayer, multichip neuromorphic systems and have been used to design sensor chips, such as retinas and cochlea, processing chips, e.g. filters, and learning chips. Furthermore, Cellular Automata is a bio-inspired processing model for problem solving. This approach divides the processing synchronous cells which change their states at the same time in order to get the solution. Ministerio de Educación y Ciencia TEC2006-11730-C03-02 Ministerio de Ciencia e Innovación TEC2009-10639-C04-02 Junta de Andalucía P06-TIC-01417

yearjournalcountryeditionlanguage
2010-07-01The 2010 International Joint Conference on Neural Networks (IJCNN)
https://doi.org/10.1109/ijcnn.2010.5596924