Real-Time recurrence plot and quantification analysis on FPGA for embedded nonlinear dynamics

Real-Time recurrence plot and quantification analysis on FPGA for embedded nonlinear dynamics | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Real-Time recurrence plot and quantification analysis on FPGA for embedded nonlinear dynamics Chunyue Li, Joseph C.S. Lai, Sebastian Oberst This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8760281/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Recurrence plots (RPs) and recurrence quantification analysis (RQA) are powerful tools for analysing the temporal behaviour of dynamical systems, but their high computational cost limits their use in real-time or resource-constrained environments. Existing GPU-accelerated software reduces offline processing time but still require large memory and energy budgets, which limits the application in embedded or streaming environments. This work presents a fully pipelined FPGA architecture that computes recurrence flags and extracts standard RQA metrics directly in hardware. Phase-space vectors are generated in streaming form using a compact circular buffer, while pairwise distances are evaluated using parallel comparison lanes with deterministic cycle-level latency. A multi-bank vector memory organisation is proposed to realise scalable parallelism to improve throughput, and core RQA measures are computed directly in hardware based on on-chip accumulators. Benchmark results indicate that the designed FPGA system delivers over ten times speedup compared to conventional CPU-based methods without precision loss. The system establishes a real-time RP framework for embedded and distributed sensing applications, including biomedical monitoring, vibration and acoustic sensing for infrastructure and network monitoring, environmental and ecological observation using distributed sensors, and underwater monitoring of marine environments. Electrical Engineering Computational Physics Recurrence plots Recurrence quantification analysis FPGA Acceleration Real-time nonlinear dynamics Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8760281","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":584011326,"identity":"f4e2225f-7c64-4784-a3bc-7a2038ff3a8f","order_by":0,"name":"Chunyue Li","email":"","orcid":"https://orcid.org/0000-0002-7189-4748","institution":"University of Technology Sydney","correspondingAuthor":false,"prefix":"","firstName":"Chunyue","middleName":"","lastName":"Li","suffix":""},{"id":584011470,"identity":"47fc1643-9e57-4f35-bb82-9c0590321820","order_by":1,"name":"Joseph C.S. 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