David Ramirez – författare

The Noah: a city-sized ship, half-way through an eight-hundred-year voyage to another planet. In a world where deeds, and even thoughts, cannot be kept secret, a man is murdered; his body so ruined that his identity must be established from DNA evidence. Within hours, all trace of the crime is swept away, hidden as though it never happened. Hana Dempsey, a mid-level bureaucrat genetically modified to use the Noah's telepathic internet, begins to investigate. Her search for the truth will uncover the impossible: a serial killer who has been operating on board for a lifetime... if not longer. And behind the killer lies a conspiracy centuries in the making.

Then least squares theory and the theory of minimum mean-squared error estimation are developed, with special attention paid to statistics that may be interpreted as coherence statistics. The chapter on subspace averaging reviews basic results and derives an order-fitting rule for determining the dimension of an average subspace.

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 coherence plays a fundamental role. Then least squares theory and the theory of minimum mean-squared error estimation are developed, with special attention paid to statistics that may be interpreted as coherence statistics. A chapter on classical hypothesis tests for covariance structure introduces the next three chapters on matched and adaptive subspace detectors. These detectors are derived from likelihood reasoning, but it is their geometries and invariances that qualify them as coherence statistics. A chapter on independence testing in space-time data sets leads to a definition of broadband coherence, and contains novel applications to cognitive radio and the analysis of cyclostationarity. The chapter on subspace averaging reviews basic results and derives an order-fitting rule for determining the dimension of an average subspace. These results are used to enumerate sources of acoustic and electromagnetic radiation and to cluster subspaces into similarity classes. The chapter on performance bounds and uncertainty quantification emphasizes the geometry of the Cramèr-Rao bound and its related information geometry.

Environmental sustainability issues in a fragile, semi-arid region and its coastal area, which experience climate changes from extreme drought conditions to the effects of hurricanes over a period of weeks to years, provide specific challenges for the ecosystems and the populations existing within the region.  The research presented focuses on the problems and some solutions specific to the South Texas-Mexico border region, on both sides of the Rio Grande, focusing on water and air pollution.