Bücher von Khaled Salah Mohamed

This book covers various, leading-edge deep learning technologies. The author discusses new applications of deep learning and gives insight into the integration of deep learning with various application domains, such as autonomous driving, augmented reality, AIOT, 5G and beyond.

This book discusses wireless communication systems from a transceiver and digital signal processing perspective. It is intended to be an advanced and thorough overview for key wireless communication technologies. A wide variety of wireless communication technologies, communication paradigms and architectures are addressed, along with state-of-the-art wireless communication standards. The author takes a practical, systems-level approach, breaking up the technical components of a wireless communication system, such as compression, encryption, channel coding, and modulation. This book combines hardware principles with practical communication system design. It provides a comprehensive perspective on emerging 5G mobile networks, explaining its architecture and key enabling technologies, such as M-MIMO, Beamforming, mmWaves, machine learning, and network slicing.  Finally, the author explores the evolution of wireless mobile networks over the next ten years towards 5G and beyond (6G), including use-cases, system requirements, challenges and opportunities.

This book provides an introduction to Bluetooth technology, with a specific focus on developing a hardware architecture for its modem. This book differs from existing content in that it presents Bluetooth Transceiver architecture suitable for implementation in an FPGA for IoT Devices.

This book provides comprehensive coverage of various Cryptography topics, while highlighting the most recent trends such as quantum, blockchain, lightweight, Chaotic and DNA cryptography.

This book discusses and compares several new trends that can be used to overcome Moore's law limitations, including Neuromorphic, Approximate, Parallel, In Memory, and Quantum Computing.

This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior. The author describes techniques to reduce significantly the time required for simulations involving large-scale ordinary differential equations, which sometimes take several days or even weeks. This method is called model order reduction (MOR), which reduces the complexity of the original large system and generates a reduced-order model (ROM) to represent the original one. Readers will gain in-depth knowledge of machine learning and model order reduction concepts, the tradeoffs involved with using various algorithms, and how to apply the techniques presented to circuit simulations and numerical analysis.Introduces machine learning algorithms at the architecture level and the algorithm levels of abstraction;Describes new, hybrid solutions for model order reduction;Presents machine learning algorithms in depth, but simply;Uses real, industrial applications to verify algorithms.

This book introduces readers to all the necessary components and knowledge to start being a vital part of the IoT revolution. Coverage includes the most important aspects of IoT architecture, the various applications of IoT, and the enabling technologies for IoT.

This book describes the life cycle process of IP cores, from specification to production, including IP modeling, verification, optimization, and protection.