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Reconfigurable Activation Functions in Integrated Optical Neural Networks

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Reconfigurable Activation Functions in Integrated Optical Neural Networks

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dc.contributor.author Rausell-Campo, Jose Roberto es_ES
dc.contributor.author Pérez-López, Daniel es_ES
dc.date.accessioned 2023-06-19T18:01:24Z
dc.date.available 2023-06-19T18:01:24Z
dc.date.issued 2022-07 es_ES
dc.identifier.issn 1077-260X es_ES
dc.identifier.uri http://hdl.handle.net/10251/194394
dc.description.abstract [EN] The implementation of nonlinear activation functions is one of the key challenges that optical neural networks face. To the date, different approaches have been proposed, including switching to digital implementations, electro-optical or all optical. In this article, we compare the response of different electro-optic architectures where part of the input optical signal is converted into the electrical domain and used to self-phase modulate the intensity of the remaining optical signal. These architectures are made up of Mach Zehnder Interferometers (MZI) and microring resonators (MRR). We have compared the corresponding transfer functions with commonly used activation functions in state-of-the-art machine learning models and carried out an in-depth analysis of the capabilities of those architectures to generate the proposed activation functions. We demonstrate that a ring assisted MZI and a two-ring assisted MZI present the highest expressivity among the proposed structures. To the best of our knowledge, this is the first time that a quantified analysis of the capabilities of optical devices to mimic state-of-the-art activation functions is presented. The obtained activation functions are benchmarked on two machine learning examples: classification task using the Iris dataset, and image recognition using the MNIST dataset. We use complex-valued feed-forward neural networks and get test accuracies of 97% and 95% respectively. es_ES
dc.description.sponsorship This work was supported in part by FPI-UPV Grant Program under Grant PAID-01-20-24 from the Universitat Politecnica de Valencia, through the Spanish MINECO Juan de la Cierva Program and in part by the H2020-ICT2019-2 Neoteric 871330 Project. es_ES
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers es_ES
dc.relation.ispartof IEEE Journal of Selected Topics in Quantum Electronics es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Optical interferometry es_ES
dc.subject Nonlinear optics es_ES
dc.subject Optical imaging es_ES
dc.subject Optical modulation es_ES
dc.subject Optical signal processing es_ES
dc.subject Optical bistability es_ES
dc.subject Adaptive optics es_ES
dc.subject Complex-valued neural networks es_ES
dc.subject Electro-optic modulation es_ES
dc.subject Machine learning es_ES
dc.subject Optical activation functions es_ES
dc.subject Optical neural networks es_ES
dc.title Reconfigurable Activation Functions in Integrated Optical Neural Networks es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/JSTQE.2022.3169833 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/871330/EU es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV-VIN//PAID-01-20-24//Fotónica integrada programable para aplicaciones de inteligencia artificial./ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia es_ES
dc.description.bibliographicCitation Rausell-Campo, JR.; Pérez-López, D. (2022). Reconfigurable Activation Functions in Integrated Optical Neural Networks. IEEE Journal of Selected Topics in Quantum Electronics. 28(4):1-13. https://doi.org/10.1109/JSTQE.2022.3169833 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1109/JSTQE.2022.3169833 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 13 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 28 es_ES
dc.description.issue 4 es_ES
dc.relation.pasarela S\469038 es_ES
dc.contributor.funder COMISION DE LAS COMUNIDADES EUROPEA es_ES
dc.contributor.funder UNIVERSIDAD POLITECNICA DE VALENCIA es_ES
upv.costeAPC 3025 es_ES


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