Statistical Signal Processing in Engineering

Statistical Signal Processing in Engineering takes a pragmatic approach in solving a set of common problems engineers and technicians encounter when processing signals. The author draws on his vast theoretical and practical experience in the field to provide a quick-solution manual for technicians and engineers, offering field-tested solutions to most problems engineers can encounter. At the same time, the book delineates the basic concepts and applied mathematics underlying each solution, so readers can go deeper into the theory to gain a better idea of the solution’s limitations and potential pitfalls, and thus tailor the best solution for the specific engineering application.

The book:

• Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing
• Is informed by the author’s vast experience as both a practitioner and teacher
• Offers a hands-on approach to solving problems in statistical signal processing
• Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering, and distributed computations
• Features numerous real-world examples from a wide range of applications showing the mathematical concepts involved in practice
• Includes MATLAB code of many of the experiments in the book

Statistical Signal Processing in Engineering is a working resource for electrical engineers, especially those working in the information and communication technology (ICT) industry. It is also a text for engineering students studying statistical signal processing at large applied mathematics post-graduate programs and advanced undergraduate programs in electrical engineering, applied statistics, and pure mathematics.