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H-infinity control and estimation of state-multiplicative linear systems
This monograph embodies a comprehensive survey of the relevant literature with basic problems being formulated and solved by applying various techniques including game theory, linear matrix inequalities and Lyapunov parameter-dependent functions.
High performance computing – HiPC 2005 ; 12th International Conference, Goa, India, December 18-21, 2005, Proceedings
Contains the refereed proceedings of the 12th International Conference on High-Performance Computing. Beginning with the keynote section and the presentation of the 2 awarded best contributions, this book is organized in topical sections on algorithms, applications, architecture, systems software, communication networks, and systems and networks.
Deep learning and computer vision in remote sensing-II
Computer vision (CV) have seen a massive rise in popularity in the remote sensing field over the last few years. This success is mostly due to the effectiveness of deep learning (DL) algorithms. However, remote sensing data acquisition and annotation, as well as information extraction from massive remote sensing data, are still challenging. This reprint collected novel developments in the field of deep learning and computer vision methods for remote sensing. Papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems, have been published. With practical examples and real-world case studies, this reprint provides a valuable resource for researchers, professionals, and students seeking to harness the power of deep learning in the field of remote sensing.
Computer Vision Beyond the Visible Spectrum
Recently, there has been a dramatic increase in the use of sensors in the non-visible bands. As a result, there is a need for existing computer vision methods and algorithms to be adapted for use with non-visible sensors, or for the development of completely new methods and systems. Computer Vision Beyond the Visible Spectrum is the first book to bring together state-of-the-art work in this area. It presents new & pioneering research across the electromagnetic spectrum in the military, commercial, and medical domains. By providing a detailed examination of each of these areas, it focuses on the development of state-of-the-art algorithms and looks at how they can be used to solve existing & new challenges within computer vision. Essential reading for academics & industrial researchers working in the area of computer vision, image processing, and medical imaging, it will also be useful background reading for advanced undergraduate & postgraduate students.
Bayesian Methods in the Search for MH370
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. The book describes particle-filter based numerical calculation of the aircraft flight-path probability distribution and validates the method using data from several of the involved aircraft’s previous flights. Finally it is shown how the Reunion Island flaperon debris find affects the search probability distribution.
Advances in UAV detection, classification and tracking
Explores the latest techniques and advancements in unmanned aerial vehicle (UAV) detection, classification, and tracking. As UAV technology continues to evolve and become more accessible, there is a growing need for effective methods to detect, identify, and track these devices in various scenarios. This reprint provides a thorough overview of the state-of-the-art approaches for UAV detection, classification, and tracking, covering both theoretical and practical aspects.The reprint begins by introducing the basics of UAVs and their various applications, followed by a detailed overview of the challenges associated with UAV detection, classification, and tracking. The authors then present the latest techniques and algorithms used in the field, including machine-learning-based approaches, computer vision techniques, and sensor fusion techniques. The reprint also covers the challenges of real-world applications, such as dealing with occlusions, sensor noise, and environmental factors.
Advances in radar systems for target detection and tracking
Radar systems can provide the all-weather and all-time detection and tracking of targets of interest, and they have been extensively applied by the remote sensing community, in applications such as geological exploration, disaster forecasting, traffic monitoring, urban planning, environmental sciences, hydrology, littoral zones, oceans, etc. This reprint contains the several advance research studies on radar systems for target detection and tracking. It includes multipath ghost suppression, maneuvering target tracking, target detection, and other topics.
