This volume fills a need in industry and universities for a comprehensive introductory text on radar principles. Well-organized and pedagogically driven, this book focuses on basic and optimum methods of realizing radar operations, covers modern applications, and provides a detailed,...

The book offers an exploration of the relationships between epistemology and probability in the work of Niels Bohr, Werner Heisenberg, and Erwin Schrödinger; in quantum mechanics; and in modern physics as a whole. It also considers the implications of these relationships and of quantum theory itself for our understanding of the nature of...

This second edition of the popular textbook contains a comprehensive course in modern probability theory. Overall, probabilistic concepts play an increasingly important role in mathematics, physics, biology, financial engineering and computer science. They help us in understanding magnetism, amorphous media, genetic diversity and the perils...

This market-leading text provides a comprehensive introduction to probability and statistics for engineering students in all specialties. Proven, accurate, and lauded for its excellent examples, Probability and Statistics for Engineering and the Sciences evidences Jay Devore's reputation as an outstanding author and leader in the...

The first half of the book is devoted to the discussion of classical statistical issues, ranging from the basic concepts of...

Artificial Intelligence (AI) is a big field, and this is a big book. We have tried to explore the full breadth of the field, which encompasses logic, probability, and continuous mathematics; perception, reasoning, learning, and action; and everything from microelectronic devices to robotic planetary explorers. The book is...

IN TRADITIONAL COMPUTER GRAPHICS, 3D objects are created using highlevel surface representations such as polygonal meshes, NURBS (nonuniform rational B-spline) patches, or subdivision surfaces. Using this modeling paradigm, visual properties of surfaces, such as color, roughness, and reflectance, are described by means of a shading...

This volume first introduces the mathematical tools necessary for understanding and working with a broad class of applied stochastic models. The toolbox includes Gaussian processes, independently scattered measures such as Gaussian white noise and Poisson random measures, stochastic integrals, compound Poisson, infinitely divisible and stable...