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Flight Dynamics Principles
The study of flight dynamics requires a thorough understanding of the theory of the stability and control of aircraft, an appreciation of flight control systems and a comprehensive grounding in the theory of automatic control. Flight Dynamics Principles provides all three in an accessible and student focussed text. Written for those coming to the subject for the first time the book is suitable as a complete first course text. It provides a secure foundation from which to move on to more advanced topics such a non-linear flight dynamics, simulation and advanced flight control, and is ideal for those on course including flight mechanics, aircraft handling qualities, aircraft stability and control. Enhances by detailed worked examples, case studies and aircraft operating condition software, this complete course text, by a renowned flight dynamicist, is widely used on aircraft engineering courses * Suitable as a complete first course text, it provides a secure foundation from which to move on to more advanced topics such a non-linear flight dynamics, simulation and advanced flight control * End of chapter exercises, detailed worked examples, and case studies aid understanding and relate concepts to real world applications * Covers key contemporary topics including all aspects of optimization, emissions, regulation and automatic flight control and UAVs * Accompanying MathCAD software source code for performance model generation and optimization
eBook
Raspberry Pi Hardware Projects 2
Raspberry Pi is a UK Non Profit with the goal of creating a new generation of computer programmers. Observing how the UK Tech Industry was kickstarted by the availability in the 1980s of relatively cheap, very programmable computers such as the ZX81, the Commodore and the BBC Micro, the Raspberry Pi Foundation designed a £15/$25 computer which encourages the user to play and to learn. Although intended for schools, it has also been adopted by hackers and geeks, and a whole ecosystem of software and hardware is being built around the Pi. With a million boards now sold, the goal of the Foundation is well underway.
eBook
Bayesian Signal Processing
Presents the Bayesian approach to statistical signal processing for a variety of useful model sets This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to “fill-in-the gaps” of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical “sanity testing” lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems. The second edition of Bayesian Signal Processing features: “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters: and the “next-generation” Bayesian particle filters Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available Problem sets included to test readers’ knowledge and help them put their new skills into practice Bayesian Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.
eBook