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COHERENCE : in signal processing and machine learning by David Ramírez, Ignacio Santamaría, Louis Scharf is a nonfiction available to read on EtoBox.

What is COHERENCE : in signal processing and machine learning about?

This book organizes principles and methods of signal processing and machine learning into the framework of coherence. The book contains a wealth of classical and modern methods of inference, some reported here for the first time. General results are applied to problems in communications, cognitive radio, passive and active radar and sonar, multi-sensor array processing, spectrum analysis, hyperspectral imaging, subspace clustering, and related. The reader will find new results for model fitting; for dimension reduction in models and ambient spaces; for detection, estimation, and space-time series analysis; for subspace averaging; and for uncertainty quantification. Throughout, the transformation invariances of statistics are clarified, geometries are illuminated, and null distributions are given where tractable. Stochastic representations are emphasized, as these are central to Monte Carlo simulations. The appendices contain a comprehensive account of matrix theory, the SVD, the multivariate normal distribution, and many of the important distributions for coherence statistics. The book begins with a review of classical results in the physical and engineering sciences where coherenc

Who reads COHERENCE : in signal processing and machine learning?

Author

David Ramírez, Ignacio Santamaría, Louis Scharf

Publisher

Springer International Publishing AG

Published

2022

Language

EN

ISBN

9783031133312

Category

nonfiction

Subjects

Engineering, Science, Stem