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  • Sách/Book

  • Low Power Architectures for IoT Applications

    • Authors: Sharma, Devendra Kumar (2023)

  • This book provides comprehensive coverage of different aspects of low-power circuit synthesis for IoT applications at various levels of the design hierarchy, starting from the layout level to the system level.
  • Sách/Book

  • Security, Trust and Privacy Models, and Architectures in IoT Environments

    • Authors: M.L. Sarné, Giuseppe (2023)

  • This book is dedicated to the issues of security, trust and privacy models, and architectures in IoT environments. The authors aim to capture the latest research and contributions from academy, industry, and other stakeholders on new security models, architectures, protocols, and standards for ensuring security, privacy, and trustworthiness to IoT systems.
  • Sách/Book

  • IoT product design and development : best practices for industrial, consumer, and business applications

    • Authors: Fattahi, Ahmad (2022)

  • This book will set up the foundation for the successful process of going about the IoT product design and management while offering specific practical and tried recommendations before, during, and after execution. It also offers a practical recipe for the endeavor by offering technological and human-related best practices and pitfalls based on numerous real-world examples. While high level technology, data, and business principles will be discussed, this book is not a deep technical guide that covers technological solutions in detail. Rather we cover the breadth of the technologies related to IoT at a high level
  • Sách/Book

  • Blogging All-in-One For Dummies

    • Authors: Bair, Lupold (2023)

  • Blogging All-in-One For Dummies is the only resource you’ll need to get started or to improve your existing blog. Learn about the most popular blogging platforms, creating content worth reading, and methods for driving traffic to your blog.
  • Sách/Book

  • Deep Neural Network Design for Radar Applications

    • Authors: - (2021)

  • The book begins with three introductory chapters on radar systems and phenomenology, machine learning principles, and optimization for training common deep neural network (DNN) architectures. Subsequently, the book summarizes radar-specific issues relating to the different domain representations in which radar data may be presented to DNNs and synthetic data generation for training dataset augmentation.
  • Sách/Book

  • Representation in Machine Learning

    • Authors: M. N. Murty (2023)

  • This book provides a concise but comprehensive guide to representation, which forms the core of Machine Learning (ML). State-of-the-art practical applications involve a number of challenges for the analysis of high-dimensional data.