Baker Mohammad

Hani Saleh

Ghada Alsuhli

Vasilis Sakellariou

Mahmoud Al-Qutayri

Thanos Stouraitis

This book provides readers a comprehensive introduction to alternative number systems for more efficient representations of Deep Neural Network (DNN) data. Various number systems (conventional/unconventional) exploited for DNNs are discussed, including Floating Point (FP), Fixed Point (FXP), Logarithmic Number System (LNS), Residue Number System (RNS), Block Floating Point Number System (BFP), Dynamic Fixed-Point Number System (DFXP) and Posit Number System (PNS). The authors explore the impact of these number systems on the performance and hardware design of DNNs, highlighting the challenges associated with each number system and various solutions that are proposed for addressing them.

Number Systems for Deep Neural Network Architectures

Mohammed Ismail

Nourhan Elsayed

Mihai Sanduleanu

This book introduces power amplifier design in 22nm FDSOI CMOS dedicated towards 5G applications at 28 GHz and presents 4 state-of-the-art power amplifier designs. The authors discuss power amplifier performance metrics, design trade-offs, and presents different power amplifier classes utilizing efficiency enhancement techniques at 28 GHz. The book presents the design process from theory, simulation, layout, and finally measurement results.

High Efficiency Power Amplifier Design for 28 GHz 5G Transmitters

Mohammad Alhawari

This book discusses the design and implementation of energy harvesting systems targeting wearable devices. The authors describe in detail the different energy harvesting sources that can be utilized for powering low-power devices in general, focusing on the best candidates for wearable applications. Coverage also includes state-of-the-art interface circuits, which can be used to accept energy from harvesters and deliver it to a device in the most efficient way. Finally, the authors present power management circuits for using multiple energy harvesting sources at the same time to power devices and to enhance efficiency of the system.

Energy Harvesting for Self-Powered Wearable Devices

Hani Saleh

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