03688nam 22005413 450 991102004120332120241128080256.0978139422863813942286359781394228652139422865197813942286451394228643(CKB)36644131300041(MiAaPQ)EBC31804606(Au-PeEL)EBL31804606(Perlego)4659669(EXLCZ)993664413130004120241128d2024 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierDynamical Behaviors of Multiweighted Complex Network Systems1st ed.Newark :John Wiley & Sons, Incorporated,2024.©2025.1 online resource (253 pages)9781394228614 1394228619 Highly comprehensive resource for studying neural networks, complex networks, synchronization, passivity, and associated applications Dynamical Behaviors of Multiweighted Complex Network Systems discusses the dynamical behaviors of various multiweighted complex dynamical networks, with detailed insight on synchronization for directed and undirected complex networks (CNs) with multiple state or delayed state couplings subject to recoverable attacks, along with passivity and synchronization for coupled neural networks with multi-weights (CNNMWs) by virtue of devised proportional-integral-derivative (PID) controllers. The book also investigates finite-time synchronization (FTS) and H-infinity synchronization for two types of coupled neural networks (CNNs) and focuses on finite-time passivity (FTP) and finite-time synchronization (FTS) for complex dynamical networks with multiple state/derivative couplings based on the proportional-derivative (PD) control method. Final chapters consider finite-time output synchronization and H-infinity output synchronization problems, and multiple weighted coupled reaction-diffusion neural networks (CRDNNs) with and without coupling delays. Other topics covered in Dynamical Behaviors of Multiweighted Complex Network Systems include: * Criteria of FTP for complex dynamical networks with multiple state couplings (CDNMSCs), formulated by utilizing the PD controller * Finite-time passivity (FTP) concepts for the spatially and temporally systems with different dimensions of output and input * FTS and finite time H-infinity synchronization problems for CDNs with multiple state/derivative couplings by utilizing state feedback control approach and selecting suitable parameter adjustment schemes * Adaptive output synchronization and output synchronization of CDNs with multiple output or output derivative couplings, and other adaptive control schemes Enabling readers to understand foundational concepts and grasp the latest research, Dynamical Behaviors of Multiweighted Complex Network Systems is essential for all who study neural networks, complex networks, synchronization, passivity, and their applications. Neural networks (Computer science)DynamicsNeural networks (Computer science)Dynamics.006.3/2Wang Jin-Liang634007Ren Shun-Yan1840609Wu Huai-Ning1840610Huang Tingwen1439128MiAaPQMiAaPQMiAaPQBOOK9911020041203321Dynamical Behaviors of Multiweighted Complex Network Systems4420197UNINA04383nam 22006135 450 991102041610332120250809130206.03-031-80949-110.1007/978-3-031-80949-1(MiAaPQ)EBC32257289(Au-PeEL)EBL32257289(CKB)40158925200041(DE-He213)978-3-031-80949-1(OCoLC)1531608017(EXLCZ)994015892520004120250809d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierConvergence of AI, Federated Learning, and Blockchain for Sustainable Development /edited by Mohit Kumar, Anand Nayyar, Ashutosh Kumar Singh, Yanhui Guo1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (519 pages)Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development,2522-87223-031-80948-3 Convergence of AI, Federated learning and Blockchain -- AI for expert system -- Natural Language processing for industry 4.0 -- Design and development of autonomous systems -- Decision-Making Techniques for Analytical Systems -- Smart Computational Techniques for IoT applications -- Federated Learning for advanced healthcare -- Federated learning for privacy preserving -- Secure computation for IoT applications -- Analysis and Implementation of Security using Federated Systems -- Development of Federated Learning Recommendation Systems -- Development of Intelligent Productive Federated Learning Systems -- AI and Federated Learning for Sustainable Development Systems Industry 4.0 -- Role of Blockchain Techniques for Sustainable Development -- Blockchain with smart contacts for real-time applications -- Trustworthy AI in Cybersecurity -- Case study based upon smart cities, home and agriculture using AI and Blockchain -- Sustainable Development using Blockchain Technology -- Traceability and Transparency issues in Transactions using Blockchain Techniques -- Emerging Trends and future directions of AI assisted Blockchain and Federated Learning for Sustainable Development Systems.This book provides current state of the art along with an insight of recent research trends and open issues, challenges, and future research direction for the academician, analyzer, researcher, writers, and authors. It also provides an opportunity to exchange knowledge in the field of IoT-enabled smart systems, Industry 4.0, networking, cyber-physical system, computing paradigms, and security with various tools and methods used for industry-oriented intelligent-based IoT applications. This advanced research edited book focuses on emerging and advancing technology-federated machine learning, blockchain, and artificial intelligence for real-time Internet of things (IoT) application to solve the real-world problems and make the life of human more conformable. The objective of the proposed book is to develop privacy preserving model for IoT applications and improve the security, privacy, reliability, and sustainability of the systems. This book motivates and enhances the quality of research and commercialization in the fields of AI, Industry 4.0, federated learning, and blockchain.Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development,2522-8722SustainabilityBlockchains (Databases)Artificial intelligenceSustainabilityBlockchainArtificial IntelligenceSustainability.Blockchains (Databases)Artificial intelligence.Sustainability.Blockchain.Artificial Intelligence.338.927Mohit Kumar1886969Nayyar Anand1379041Singh Ashutosh Kumar1785463Guo Yanhui1365700MiAaPQMiAaPQMiAaPQBOOK9911020416103321Convergence of AI, Federated Learning, and Blockchain for Sustainable Development4529884UNINA