Convergence Properties of Recurrence Sequences PDF Download
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Author: R. J. Kooman (mathématicien)
Publisher:
ISBN:
Category : Continued fractions
Languages : en
Pages : 126
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Book Description
Author: R. J. Kooman (mathématicien)
Publisher:
ISBN:
Category : Continued fractions
Languages : en
Pages : 126
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Book Description
Author: Robert Jan Kooman
Publisher:
ISBN:
Category :
Languages : en
Pages : 102
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Book Description
Author: Robert J. Kooman
Publisher:
ISBN:
Category : Sequences (Mathematics)
Languages : en
Pages : 102
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Book Description
Author: Michael Drmota
Publisher: Springer
ISBN: 354068333X
Category : Mathematics
Languages : en
Pages : 517
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Book Description
The main purpose of this book is to give an overview of the developments during the last 20 years in the theory of uniformly distributed sequences. The authors focus on various aspects such as special sequences, metric theory, geometric concepts of discrepancy, irregularities of distribution, continuous uniform distribution and uniform distribution in discrete spaces. Specific applications are presented in detail: numerical integration, spherical designs, random number generation and mathematical finance. Furthermore over 1000 references are collected and discussed. While written in the style of a research monograph, the book is readable with basic knowledge in analysis, number theory and measure theory.
Author: R.L. Graham
Publisher: Elsevier
ISBN: 044488002X
Category : Business & Economics
Languages : en
Pages : 1283
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Book Description
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799804151
Category : Computers
Languages : en
Pages : 1671
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Book Description
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.
Author: R M Ali
Publisher: World Scientific
ISBN: 9814549738
Category :
Languages : en
Pages : 374
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Book Description
The topics discussed at the conference revolved around the interaction of computational methods and theoretical function theory, as well as recent advances and developments in both fields. The talks ranged from analytic function theory to approximation theory to numerical conformal mapping and other computational methods.
Author: Annie A.M. Cuyt
Publisher: Springer Science & Business Media
ISBN: 1402069499
Category : Mathematics
Languages : en
Pages : 430
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Book Description
Special functions are pervasive in all fields of science and industry. The most well-known application areas are in physics, engineering, chemistry, computer science and statistics. Because of their importance, several books and websites (see for instance http: functions.wolfram.com) and a large collection of papers have been devoted to these functions. Of the standard work on the subject, the Handbook of mathematical functions with formulas, graphs and mathematical tables edited by Milton Abramowitz and Irene Stegun, the American National Institute of Standards claims to have sold over 700 000 copies! But so far no project has been devoted to the systematic study of continued fraction representations for these functions. This handbook is the result of such an endeavour. We emphasise that only 10% of the continued fractions contained in this book, can also be found in the Abramowitz and Stegun project or at the Wolfram website!
Author: Graham Everest
Publisher: American Mathematical Soc.
ISBN: 1470423154
Category :
Languages : en
Pages : 318
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Book Description
Recurrence sequences are of great intrinsic interest and have been a central part of number theory for many years. Moreover, these sequences appear almost everywhere in mathematics and computer science. This book surveys the modern theory of linear recurrence sequences and their generalizations. Particular emphasis is placed on the dramatic impact that sophisticated methods from Diophantine analysis and transcendence theory have had on the subject. Related work on bilinear recurrences and an emerging connection between recurrences and graph theory are covered. Applications and links to other areas of mathematics are described, including combinatorics, dynamical systems and cryptography, and computer science. The book is suitable for researchers interested in number theory, combinatorics, and graph theory.
Author: V.V. Buldygin
Publisher: Springer Science & Business Media
ISBN: 9401155682
Category : Mathematics
Languages : en
Pages : 512
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Book Description
Limit theorems for random sequences may conventionally be divided into two large parts, one of them dealing with convergence of distributions (weak limit theorems) and the other, with almost sure convergence, that is to say, with asymptotic prop erties of almost all sample paths of the sequences involved (strong limit theorems). Although either of these directions is closely related to another one, each of them has its own range of specific problems, as well as the own methodology for solving the underlying problems. This book is devoted to the second of the above mentioned lines, which means that we study asymptotic behaviour of almost all sample paths of linearly transformed sums of independent random variables, vectors, and elements taking values in topological vector spaces. In the classical works of P.Levy, A.Ya.Khintchine, A.N.Kolmogorov, P.Hartman, A.Wintner, W.Feller, Yu.V.Prokhorov, and M.Loeve, the theory of almost sure asymptotic behaviour of increasing scalar-normed sums of independent random vari ables was constructed. This theory not only provides conditions of the almost sure convergence of series of independent random variables, but also studies different ver sions of the strong law of large numbers and the law of the iterated logarithm. One should point out that, even in this traditional framework, there are still problems which remain open, while many definitive results have been obtained quite recently.
