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The Variational Bayes Method in Signal ProcessingThis is the first book-length treatment of the Variational Bayes (VB) approximation in signal processing. It has been written as a self-contained, self-learning guide for academic and industrial research groups in signal processing, data analysis, machine learning, identification and control. It reviews the VB distributional approximation, showing... | | | | Handbook of Mathematical Models in Computer VisionDavid Marr's theory was a pioneering step towards understanding visual perception. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical... |
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Multiscale Theory of Composites and Random Media
This is the first book to introduce Green-function-based multiscale theory and the corresponding finite element method, which are readily applicable to composites and random media. The methodology is considered to be the one that most effectively tackles the uncertainty of stress propagation in complex heterogeneities of random... | | Mathematical Problems in Image Processing
It is surprising when we realize just how much we are surrounded by images.
Images allow us not only to perform complex tasks on a daily basis, but also
to communicate, transmit information, represent and understand the world
around us. Just think, for instance about digital television, medical imagery,
video-surveillance, etc.... | | Applied Calculus of Variations for Engineers
The subject of calculus of variations is to find optimal solutions to engineering problems where the optimum may be a certain quantity, a shape, or a function. Applied Calculus of Variations for Engineers addresses this very important mathematical area applicable to many engineering disciplines. Its unique,... |
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