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Tracking with Particle Filter for High-dimensional Observation and State Spaces

This title concerns the use of a particle filter framework to track objects defined in high-dimensional state-spaces using high-dimensional;

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Understanding High-Dimensional Spaces

High-dimensional spaces arise as a way of modelling datasets with many attributes. Such a dataset can be directly represented in a space;

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Topological Vector Spaces and Their Applications

-dimensional spaces. These applications are a central aspect of the book, which is why it is different from the wide range of existing texts on;

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Introduction to Ramsey Spaces (AM-174)

useful. Introduction to Ramsey Spaces presents in a systematic way a method for building higher-dimensional Ramsey spaces from basic one;

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Finite Elements

scalar parabolic problems, object-oriented finite element algorithms, efficient implementation techniques, and high dimensional parabolic;

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Symposium on Infinite Dimensional Topology. (AM-69), Volume 69

linear spaces, fixed point theory in infinite dimensional spaces, infinite dimensional differential topology, and infinite dimensional pointset;

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Topology of Infinite Dimensional Manifolds

An infinite-dimensional manifold is a topological manifold modeled on some infinite-dimensional homogeneous space called a model space;

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Topology of Infinite Dimensional Manifolds

An infinite-dimensional manifold is a topological manifold modeled on some infinite-dimensional homogeneous space called a model space;

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Infinite-Dimensional Dynamical Systems

-Stokes equations, two examples that are treated in detail. A lengthy chapter on Sobolev spaces provides the framework that allows a rigorous;

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Infinite-Dimensional Dynamical Systems

-Stokes equations, two examples that are treated in detail. A lengthy chapter on Sobolev spaces provides the framework that allows a rigorous;

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Algorithmic Learning in a Random World

used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data;

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Algorithmic Learning in a Random World

used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data;

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Feature Selection for High-Dimensional Data

-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces;

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Functional Adaptive Control

, unpredictable disturbances, multi-modality and high dimensional spaces.;

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Topology as Fluid Geometry

This is the second of a three volume collection devoted to the geometry, topology, and curvature of 2-dimensional spaces. The collection;

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Bayesian and High-Dimensional Global Optimization

portion of this book is devoted to an analysis of high-dimensional global optimization problems and the so-called 'curse of dimensionality'. An;

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Finite-Dimensional Vector Spaces

transformations on finite dimensional vector spaces by the methods of more general theories. The idea is to emphasize the simple geometric notions common;

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Finite-Dimensional Vector Spaces

transformations on finite dimensional vector spaces by the methods of more general theories. The idea is to emphasize the simple geometric notions common;

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Finite Dimensional Vector Spaces. (AM-7), Volume 7

was one of von Neumann's inspiring lectures that spurred Halmos to write Finite Dimensional Vector Spaces. The book brought him instant fame as an;

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Elements Of Mathematical Theory Of Evolutionary Equations In Banach Spaces

considered are the questions on existence and approximate construction of periodic solutions for difference equations in infinite-dimensional spaces;

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From Euclidean to Hilbert Spaces - Introduction to Functional Analysis and its Applications

From Euclidian to Hilbert Spaces analyzes the transition from finite dimensional Euclidian spaces to infinite-dimensional Hilbert spaces, a;

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Fundamentals of Low-Dimensional Carbon Nanomaterials

Symposium C, 'Fundamentals of Low-Dimensional Carbon Nanomaterials', was held November 29-December 3 at the 2010 MRS Fall Meeting in Boston;

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Linear and Quasilinear Parabolic Problems: Volume II: Function Spaces

infinite-dimensional Banach spaces as targets. It especially highlights the most important subclasses of Besov spaces, namely Slobodeckii and;

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Mathematical Foundations of Infinite-Dimensional Statistical Models

In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood;

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Tools for Infinite Dimensional Analysis

roadblock. The background material primarily stems from an abstract subject known as infinite dimensional topological vector spaces. While this;

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7T MRI, An Issue of Magnetic Resonance Imaging Clinics of North America

: Ultra High Field MRI of the Human Eye and Orbit at 7T; 7T MRI of Perivascular Spaces; 7T MRI in Non Lesional Epilepsy/ Perivascular Spaces; 7T;

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Nanotechnologies and Clusters in the Spaces of Higher Dimension

aspects of the production of intermetallic clusters in high dimensional spaces using nanotechnology. Featuring coverage on a broad range of topics;

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