Spatiotemporal Chaos in Exponential Cosine Polynomial Nonlinear Coupling and its Application in Adaptive Multi-Image Encryption with Autoencoder

Spatiotemporal Chaos in Exponential Cosine Polynomial Nonlinear Coupling and its Application in Adaptive Multi-Image Encryption with Autoencoder | 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 Spatiotemporal Chaos in Exponential Cosine Polynomial Nonlinear Coupling and its Application in Adaptive Multi-Image Encryption with Autoencoder Dawei Ding, Tao Liu, Hong Cheng, Zongli Yang, Xiang Liu, Haitao Zhou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7051315/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Nonlinear Dynamics → Version 1 posted 17 You are reading this latest preprint version Abstract Spatiotemporal chaotic systems possess high dimensional dynamics and strong spatial and temporal diffusion capabilities, making them highly suitable for secure communication. However, many existing models suffer from limited chaotic regions and insufficient security. To address these issues, a novel spatiotemporal chaotic system featuring exponential cosine polynomial nonlinear coupling and dynamic nonlocal interactions is constructed as the core of an adaptive multi-image encryption scheme. The proposed model, named Exponential Cosine Polynomial Coupled Map Lattice (ECPCML), enhances chaotic behavior through nonlocal coupling and cosine-based coefficients with dynamic adjustment, resulting in a wider chaotic region and higher unpredictability. To further enhance security, a 3D Knight’s Tour Scrambling (3D-KTS) algorithm is employed to realize cross channel scrambling along 24 movement directions, followed by Affine Pixel Diffusion (APD) for pixel level protection. An autoencoder is integrated for lossy compression to improve transmission efficiency without significantly degrading image quality. Additionally, a multi-image fusion strategy enables simultaneous encryption of multiple images with varying sizes and channels. Experimental results and comparative analyses confirm that the proposed scheme achieves favorable performance in security, compression efficiency, and resistance to chosen-plaintext attacks, demonstrating its potential for secure image transmission in complex network environments. Spatiotemporal chaos Nonlinear coupling ECPCML model Multiple images encryption Autoencoder 3D Knight’s tour Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Nonlinear Dynamics → Version 1 posted Editorial decision: Revision requested 25 Nov, 2025 Reviews received at journal 25 Nov, 2025 Reviewers agreed at journal 23 Nov, 2025 Reviewers agreed at journal 22 Nov, 2025 Reviewers agreed at journal 21 Nov, 2025 Reviewers agreed at journal 21 Nov, 2025 Reviews received at journal 15 Nov, 2025 Reviewers agreed at journal 15 Nov, 2025 Reviews received at journal 19 Jul, 2025 Reviewers agreed at journal 10 Jul, 2025 Reviewers agreed at journal 10 Jul, 2025 Reviewers agreed at journal 10 Jul, 2025 Reviewers agreed at journal 08 Jul, 2025 Reviewers invited by journal 08 Jul, 2025 Editor assigned by journal 07 Jul, 2025 Submission checks completed at journal 07 Jul, 2025 First submitted to journal 05 Jul, 2025 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. 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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-7051315","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482690333,"identity":"6b76e213-07cf-4042-be75-7fdf3aa42dd8","order_by":0,"name":"Dawei Ding","email":"","orcid":"","institution":"Anhui University","correspondingAuthor":false,"prefix":"","firstName":"Dawei","middleName":"","lastName":"Ding","suffix":""},{"id":482690334,"identity":"8ea6b45b-347f-409e-88ae-cd368de51603","order_by":1,"name":"Tao Liu","email":"","orcid":"","institution":"Anhui 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