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Books in Mathematics

The Mathematics collection presents a range of foundational and advanced research content across applied and discrete mathematics, including fields such as Computational Mathematics; Differential Equations; Linear Algebra; Modelling & Simulation; Numerical Analysis; Probability & Statistics.

  • University Education in Computing Science

    Proceedings of a Conference on Graduate Academic and Related Research Programs in Computing Science, Held at the State University of New York at Stony Brook, June 1967
    • 1st Edition
    • Aaron Finerman
    • English
    University Education in Computing Science documents the proceedings of a conference on graduate academic and related research programs in computing science, held at the State University of New York at Stony Brook on June 8, 1967. This book provides a comprehensive study of the role of the computing sciences as an academic program, including its organizational structure and relationship to the computing center. The undergraduate education in computing science and operational policies of university computing centers are also elaborated. Other topics include the graduate computer science program at American universities, dilemma of computer sciences, and science and engineering of information. The industry's view of computing science and doctoral program in computing science are likewise covered. This publication is suitable for educational, industrial, and governmental organizations concerned with education related to computing science.

  • Stochastic Differential Equations and Applications

    Volume 2
    • 1st Edition
    • Avner Friedman
    • Z. W. Birnbaum + 1 more
    • English
    Stochastic Differential Equations and Applications, Volume 2 is an eight-chapter text that focuses on the practical aspects of stochastic differential equations. This volume begins with a presentation of the auxiliary results in partial differential equations that are needed in the sequel. The succeeding chapters describe the behavior of the sample paths of solutions of stochastic differential equations. These topics are followed by a consideration of an issue whether the paths can hit a given set with positive probability, as well as the stability of paths about a given manifold and with spiraling of paths about this manifold. Other chapters deal with the applications to partial equations, specifically with the Dirichlet problem for degenerate elliptic equations. These chapters also explore the questions of singular perturbations and the existence of fundamental solutions for degenerate parabolic equations. The final chapters discuss stopping time problems, stochastic games, and stochastic differential games. This book is intended primarily to undergraduate and graduate mathematics students.

  • Topics in Stochastic Processes

    Probability and Mathematical Statistics: A Series of Monographs and Textbooks
    • 1st Edition
    • Robert B. Ash + 1 more
    • Z. W. Birnbaum + 1 more
    • English
    Topics in Stochastic Processes covers specific processes that have a definite physical interpretation and that explicit numerical results can be obtained. This book contains five chapters and begins with the L2 stochastic processes and the concept of prediction theory. The next chapter discusses the principles of ergodic theorem to real analysis, Markov chains, and information theory. Another chapter deals with the sample function behavior of continuous parameter processes. This chapter also explores the general properties of Martingales and Markov processes, as well as the one-dimensional Brownian motion. The aim of this chapter is to illustrate those concepts and constructions that are basic in any discussion of continuous parameter processes, and to provide insights to more advanced material on Markov processes and potential theory. The final chapter demonstrates the use of theory of continuous parameter processes to develop the Itô stochastic integral. This chapter also provides the solution of stochastic differential equations. This book will be of great value to mathematicians, engineers, and physicists.

  • Tables of Generalized Airy Functions for the Asymptotic Solution of the Differential Equation

    Mathematical Tables Series
    • 1st Edition
    • L. N. Nosova + 1 more
    • English
    Tables of Generalized Airy Functions for the Asymptotic Solution of the Differential Equations contains tables of the special functions, namely, the generalized Airy functions, and their first derivatives, for real and pure imaginary values. The tables are useful for calculations on toroidal shells, laminae, rode, and for the solution of certain other problems of mathematical physics. The values of the functions were computed on the "Strela" highspeed electronic computer. This book will be of great value to mathematicians, researchers, and students.

  • Tables of Laguerre Polynomials and Functions

    Mathematical Tables Series, Vol. 39
    • 1st Edition
    • V.S. Aizenshtadt + 2 more
    • English
    Tables of Laguerre Polynomials and Functions contains the values of Laguerre polynomials and Laguerre functions for n = 2 , 3 , . . . , 7 ; s = 0(0.1) 1; x = 0(0.1) 10(0.2) 30, and the zeroes and coefficients of the polynomials for n = 2 (1) 10 and s = 0(0.05) 1. The book also explains the Laguerre polynomials, their properties, Laguerre functions, and the tabulation of the Laguerre polynomials and functions. The book contains three tables: tables of values of Laguerre polynomials and functions, tables of the coefficients of the polynomials, and tables of their roots. The first table consists of six parts arranged successively in the ascending order of the degree n. Researchers have calculated the tables for a wider range of values of the parameters n, s and x (n = 2(1) 10, s = 0(0.05) 1, x = 0(0.1) 10(0.2) 30(0.5) 80) using computers at the Institute of Mathematics and Computer Technology of the Byelorussian Academy of Sciences and the Computer Centre of the Academy of Sciences of the U.S.S.R. Scientists and investigators at computer centers, research institutes, and engineering organizations will find the book highly valuable.

  • The Laws of Large Numbers

    • 1st Edition
    • Pál Révész
    • Z. W. Birnbaum + 1 more
    • English
    The Law of Large Numbers deals with three types of law of large numbers according to the following convergences: stochastic, mean, and convergence with probability 1. The book also investigates the rate of convergence and the laws of the iterated logarithm. It reviews measure theory, probability theory, stochastic processes, ergodic theory, orthogonal series, Huber spaces, Banach spaces, as well as the special concepts and general theorems of the laws of large numbers. The text discusses the laws of large numbers of different classes of stochastic processes, such as independent random variables, orthogonal random variables, stationary sequences, symmetrically dependent random variables and their generalizations, and also Markov chains. It presents other laws of large numbers for subsequences of sequences of random variables, including some general laws of large numbers which are not related to any concrete class of stochastic processes. The text cites applications of the theorems, as in numbers theory, statistics, and information theory. The text is suitable for mathematicians, economists, scientists, statisticians, or researchers involved with the probability and relative frequency of large numbers.

  • Human and Machine Vision

    • 1st Edition
    • Jacob Beck + 2 more
    • English
    Human and Machine Vision provides information pertinent to an interdisciplinary program of research in visual perception. This book presents a psychophysical study of the human visual system, which provides insights on how to model the flexibility required by a general-purpose visual system. Organized into 17 chapters, this book begins with an overview of how a visual display is segmented into components on the basis of textual differences. This text then proposes three criteria for judging representations of shape. Other chapters consider an increased use of machine vision programs as models of human vision and of data from human vision in developing programs for machine vision. This book discusses as well the diversity and flexibility of systems for representing visual information. The final chapter deals with dot patterns and discusses the process of interring orientation information from collections of them. This book is a valuable resource for psychologists, neurophysiologists, and computer scientists.

  • Parallel Sorting Algorithms

    • 1st Edition
    • Selim G. Akl
    • Werner Rheinboldt
    • English
    Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the respective primary memories of the computers (random access memory), or in a single shared memory. SIMD processors communicate through an interconnection network or the processors communicate through a common and shared memory. The text also investigates the case of external sorting in which the sequence to be sorted is bigger than the available primary memory. In this case, the algorithms used in external sorting is very similar to those used to describe internal sorting, that is, when the sequence can fit in the primary memory, The book explains that an algorithm can reach its optimum possible operating time for sorting when it is running on a particular set of architecture, depending on a constant multiplicative factor. The text is suitable for computer engineers and scientists interested in parallel algorithms.

  • Self-Validating Numerics for Function Space Problems

    Computation with Guarantees for Differential and Integral Equations
    • 1st Edition
    • Edgar W. Kaucher + 1 more
    • Werner Rheinboldt
    • English
    Self-Validating Numerics for Function Space Problems describes the development of computational methods for solving function space problems, including differential, integral, and function equations. This seven-chapter text highlights three approaches, namely, the E-methods, ultra-arithmetic, and computer arithmetic. After a brief overview of the different self-validating approaches, this book goes on introducing the mathematical preliminaries consisting principally of fixed-point theorems and the computational context for the development of validating methods in function spaces. The subsequent chapters deals with the development and application of point of view of ultra-arithmetic and the constructs of function-space arithmetic spaces, such as spaces, bases, rounding, and approximate operations. These topics are followed by discussion of the iterative residual correction methods for function problems and the requirements of a programming language needed to make the tools and constructs of the methodology available in actual practice on a computer. The last chapter describes the techniques for adapting the methodologies to a computer, including the self-validating results for specific problems. This book will prove useful to mathematicians and advance mathematics students.

  • Decomposition of Multivariate Probabilities

    • 1st Edition
    • Roger Cuppens
    • Z. W. Birnbaum + 1 more
    • English
    Decomposition of Multivariate Probability is a nine-chapter text that focuses on the problem of multivariate characteristic functions. After a brief introduction to some useful results on measures and integrals, this book goes on dealing with the classical theory and the Fourier-Stieltjes transforms of signed measures. The succeeding chapters explore the multivariate extension of the well-known Paley-Wiener theorem on functions that are entire of exponential type and square-integrable; the theory of infinitely divisible probabilities and the classical results of Hin?in; and the decompositions of analytic characteristic functions. Other chapters are devoted to the important problem of the description of a specific class on n-variate probabilities without indecomposable factors. The final chapter studies the problem of ?-decomposition of multivariate characteristic functions. This book will prove useful to mathematicians and advance undergraduate and graduate students.

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