The latest developments in the area of RF Sensors and Sensor Networks such as for manufacturing, structural health, security monitoring, transportation, and location tracking systems

This invaluable resource introduces progressive techniques for the creation of sophisticated reflectionless filter topologies that have identically zero reflection coefficient at all frequencies. Practical implementations are discussed along with their advantages when compared to classical absorptive filters and their benefits in real-world systems such as up/down converters, multiplier chains, broadband amplifiers, analog-to-digital converters, and time-domain applications. This book offers insight into the innovative process of developing reflectionless filters from first principles using both lumped elements and transmission lines. Tools for the creation of reflectionless multiplexers, matched sloped equalizers, and advanced, high-order, and nonplanar topologies are also presented.

This edited book is the first to focus on metrology for current and future wireless communication technologies. It presents a comprehensive overview of the state-of-the-art measurement capabilities, testbeds and relevant R&D activities for 5G and emerging wireless technologies at a wide range of frequencies up to THz frequency bands.

A thorough treatment of energy harvesting technologies, highlighting radio frequency (RF) and hybrid-multiple technology harvesting. The authors explain the principles of solar, thermal, kinetic, and electromagnetic energy harvesting, address design challenges, and describe applications. The volume features an introduction to switched mode power converters and energy storage and summarizes the challenges of different system implementations, from wireless transceivers to backscatter communication systems and ambient backscattering. This practical resource is essential for researchers and graduate students in the field of communications and sensor technology, in addition to practitioners working in these fields.

Recently organized competitions have been instrumental in pushing the state-of-the-art in machine learning, establishing benchmarks to fairly evaluate methods, and identifying techniques that really work. This volume in the Challenges in Machine Learning series harvests three years of effort of hundreds of researchers who have participated in three competitions organized around five datasets from various application domains, designed to explore issues of data representation, model selection, and performance prediction.