Gaussian Random Functions PDF Download
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Author | : M.A. Lifshits |
Publisher | : Springer Science & Business Media |
Total Pages | : 347 |
Release | : 2013-03-09 |
Genre | : Mathematics |
ISBN | : 9401584745 |
Download Gaussian Random Functions Book in PDF, ePub and Kindle
It is well known that the normal distribution is the most pleasant, one can even say, an exemplary object in the probability theory. It combines almost all conceivable nice properties that a distribution may ever have: symmetry, stability, indecomposability, a regular tail behavior, etc. Gaussian measures (the distributions of Gaussian random functions), as infinite-dimensional analogues of tht
Author | : Marvin K. Simon |
Publisher | : Springer Science & Business Media |
Total Pages | : 218 |
Release | : 2007-05-24 |
Genre | : Mathematics |
ISBN | : 0387476946 |
Download Probability Distributions Involving Gaussian Random Variables Book in PDF, ePub and Kindle
This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling. Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume.
Author | : Carl Edward Rasmussen |
Publisher | : MIT Press |
Total Pages | : 266 |
Release | : 2005-11-23 |
Genre | : Computers |
ISBN | : 026218253X |
Download Gaussian Processes for Machine Learning Book in PDF, ePub and Kindle
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
Author | : I.A. Ibragimov |
Publisher | : Springer Science & Business Media |
Total Pages | : 285 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461262755 |
Download Gaussian Random Processes Book in PDF, ePub and Kindle
The book deals mainly with three problems involving Gaussian stationary processes. The first problem consists of clarifying the conditions for mutual absolute continuity (equivalence) of probability distributions of a "random process segment" and of finding effective formulas for densities of the equiva lent distributions. Our second problem is to describe the classes of spectral measures corresponding in some sense to regular stationary processes (in par ticular, satisfying the well-known "strong mixing condition") as well as to describe the subclasses associated with "mixing rate". The third problem involves estimation of an unknown mean value of a random process, this random process being stationary except for its mean, i. e. , it is the problem of "distinguishing a signal from stationary noise". Furthermore, we give here auxiliary information (on distributions in Hilbert spaces, properties of sam ple functions, theorems on functions of a complex variable, etc. ). Since 1958 many mathematicians have studied the problem of equivalence of various infinite-dimensional Gaussian distributions (detailed and sys tematic presentation of the basic results can be found, for instance, in [23]). In this book we have considered Gaussian stationary processes and arrived, we believe, at rather definite solutions. The second problem mentioned above is closely related with problems involving ergodic theory of Gaussian dynamic systems as well as prediction theory of stationary processes.
Author | : John Ben Hough |
Publisher | : American Mathematical Soc. |
Total Pages | : 170 |
Release | : 2009 |
Genre | : Mathematics |
ISBN | : 0821843737 |
Download Zeros of Gaussian Analytic Functions and Determinantal Point Processes Book in PDF, ePub and Kindle
Examines in some depth two important classes of point processes, determinantal processes and 'Gaussian zeros', i.e., zeros of random analytic functions with Gaussian coefficients. This title presents a primer on modern techniques on the interface of probability and analysis.
Author | : Ryōgo Hirota |
Publisher | : |
Total Pages | : |
Release | : 1961 |
Genre | : Quantum theory |
ISBN | : |
Download The Grand Partition Function as Average of a Functional of Gaussian Random Functions Book in PDF, ePub and Kindle
Author | : A. J. F. SIEGERT |
Publisher | : |
Total Pages | : 1 |
Release | : 1960 |
Genre | : |
ISBN | : |
Download Partition Functions as Averages of Functionals of Gaussian Random Functions Book in PDF, ePub and Kindle
Author | : Roman Vershynin |
Publisher | : Cambridge University Press |
Total Pages | : 299 |
Release | : 2018-09-27 |
Genre | : Business & Economics |
ISBN | : 1108415199 |
Download High-Dimensional Probability Book in PDF, ePub and Kindle
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Author | : Christian Lantuejoul |
Publisher | : Springer Science & Business Media |
Total Pages | : 262 |
Release | : 2013-06-29 |
Genre | : Mathematics |
ISBN | : 3662048086 |
Download Geostatistical Simulation Book in PDF, ePub and Kindle
This book deals with the estimation of natural resources using the Monte Carlo methodology. It includes a set of tools to describe the morphological, statistical and stereological properties of spatial random models. Furthermore, the author presents a wide range of spatial models, including random sets and functions, point processes and object populations applicable to the geosciences. The text is based on a series of courses given in the USA and Latin America to civil, mining and petroleum engineers as well as graduate students in statistics. It is the first book to discuss the geostatistical simulation techniques in such a specific way.
Author | : Robert J. Adler |
Publisher | : SIAM |
Total Pages | : 295 |
Release | : 2010-01-28 |
Genre | : Mathematics |
ISBN | : 0898716934 |
Download The Geometry of Random Fields Book in PDF, ePub and Kindle
An important treatment of the geometric properties of sets generated by random fields, including a comprehensive treatment of the mathematical basics of random fields in general. It is a standard reference for all researchers with an interest in random fields, whether they be theoreticians or come from applied areas.