This book is an up-to-date compendium on spacecraft attitude and orbit control (AOC) that offers a systematic and complete treatment of the subject with the aim of imparting the theoretical and practical knowledge that is required by designers, engineers, and researchers. After an introduction on the kinematics of the flexible and agile space vehicles, the modern architecture and functions of an AOC system are described and the main AOC modes reviewed with possible design solutions and examples.

The work presented in this book focuses on modeling audiovisual quality as perceived by the users of IP-based solutions for video communication like videotelephony. It also extends the current framework for the parametric prediction of audiovisual call quality. The book addresses several aspects related to the quality perception of entire video calls, namely, the quality estimation of the single audio and video modalities in an interactive context, the audiovisual quality integration of these modalities and the temporal pooling of short sample-based quality scores to account for the perceptual quality impact of time-varying degradations.

This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths. It provides details of how the probabilistic models of aircraft flight dynamics, satellite communication system measurements, environmental effects and radar data were constructed and calibrated. The probability distribution was used to define the search zone in the southern Indian Ocean.

Smart City and sensing platforms are considered some of the most significant topics in the Internet of Things (IoT). Sensors are at the heart of the IoT, and their development is a key issue if such concepts are to achieve their full potential.

This book presents and discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a renaissance in interest in neural networks, with applications including image and speech processing, data analytics, robotics, healthcare monitoring, and IoT solutions.