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Books in Mathematics and applied mathematics

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111-120 of 2229 results in All results

Computational Analysis of Structured Media

  • 1st Edition
  • September 11, 2017
  • Simon Gluzman + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 1 0 4 6 - 1
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 1 0 4 7 - 8
Computational Analysis of Structured Media presents a systematical approach to analytical formulae for the effective properties of deterministic and random composites. Schwarz’s method and functional equations yield for use in symbolic-numeric computations relevant to the effective properties. The work is primarily concerned with constructive topics of boundary value problems, complex analysis, and their applications to composites. Symbolic-numerical computations are widely used to deduce new formulae interesting for applied mathematicians and engineers. The main line of presentation is the investigation of two-phase 2D composites with non-overlapping inclusions randomly embedded in matrices.

Portfolio Diversification

  • 1st Edition
  • September 1, 2017
  • Francois-Serge Lhabitant
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 1 9 1 - 8
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 1 7 8 6 - 9
Portfolio Diversification provides an update on the practice of combining several risky investments in a portfolio with the goal of reducing the portfolio's overall risk. In this book, readers will find a comprehensive introduction and analysis of various dimensions of portfolio diversification (assets, maturities, industries, countries, etc.), along with time diversification strategies (long term vs. short term diversification) and diversification using other risk measures than variance. Several tools to quantify and implement optimal diversification are discussed and illustrated.

Inference for Heavy-Tailed Data

  • 1st Edition
  • August 11, 2017
  • Liang Peng + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 4 6 7 6 - 0
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 4 7 5 0 - 7
Heavy tailed data appears frequently in social science, internet traffic, insurance and finance. Statistical inference has been studied for many years, which includes recent bias-reduction estimation for tail index and high quantiles with applications in risk management, empirical likelihood based interval estimation for tail index and high quantiles, hypothesis tests for heavy tails, the choice of sample fraction in tail index and high quantile inference. These results for independent data, dependent data, linear time series and nonlinear time series are scattered in different statistics journals. Inference for Heavy-Tailed Data Analysis puts these methods into a single place with a clear picture on learning and using these techniques.

Introduction to Nature-Inspired Optimization

  • 1st Edition
  • August 10, 2017
  • George Lindfield + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 3 6 3 6 - 5
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 3 6 6 6 - 2
Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization.

Fundamentals of Advanced Mathematics 1

  • 1st Edition
  • July 1, 2017
  • Henri Bourles
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 1 7 3 - 4
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 2 1 1 2 - 5
This precis, comprised of three volumes, of which this book is the first, exposes the mathematical elements which make up the foundations of a number of contemporary scientific methods: modern theory on systems, physics and engineering. This first volume focuses primarily on algebraic questions: categories and functors, groups, rings, modules and algebra. Notions are introduced in a general framework and then studied in the context of commutative and homological algebra; their application in algebraic topology and geometry is therefore developed. These notions play an essential role in algebraic analysis (analytico-algebraic systems theory of ordinary or partial linear differential equations). The book concludes with a study of modules over the main types of rings, the rational canonical form of matrices, the (commutative) theory of elemental divisors and their application in systems of linear differential equations with constant coefficients.

Analysis of Step-Stress Models

  • 1st Edition
  • June 15, 2017
  • Debasis Kundu + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 9 7 1 3 - 7
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 1 2 4 0 - 6
Analysis of Step-Stress Models: Existing Results and Some Recent Developments describes, in detail, the step-stress models and related topics that have received significant attention in the last few years. Although two books, Bagdonavicius and Nikulin (2001) and Nelson (1990), on general accelerated life testing models are available, no specific book is available on step-stress models. Due to the importance of this particular topic, Balakrishnan (2009) provided an excellent review for exponential step-stress models. The scope of this book is much more, providing the inferential issues for different probability models, both from the frequentist and Bayesian points-of-view.

Principles of Mathematical Modeling

  • 3rd Edition
  • June 1, 2017
  • Clive Dym
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 4 7 4 4 - 6
Principles of Mathematical Modeling 3rd edition describes, in clear and simple language, the essential corpus of modelling principles, and then builds on them with a set of foundational tools including dimensional analysis, scaling techniques, and approximation and validation techniques. The second half demonstrates the latest applications for these tools to a broad variety of subjects, including exponential growth and decay in fields ranging from biology to economics, traffic flow, free and forced vibration of mechanical and other systems, and optimization problems in biology, structures, and social decision making.　 The work will be particularly of interest to scientific and professional students of various stripes who depend heavily on concepts of mathematical modeling. In an age where many modelling applications turn increasingly to the cloud, author Clive Dym believes that students need to understand and ‘own’ the underlying mathematics that computers are doing on their behalf. This work aims to continue to engage the student reader in developing a foundational understanding of the subject that will serve them well into their careers.　Prospective students should have already completed courses in elementary algebra, trigonometry, and first-year calculus and have some familiarity with differential equations and basic physics.

Foundations of Mathematical System Dynamics

  • 1st Edition
  • Volume 2
  • May 25, 2017
  • George J. Klir
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 8 6 9 7 - 6
This book is a foundational study of causality as conceived in the mathematical sciences. It is shown that modern mathematical dynamics involves a formulation of the fundamental concept of causality, and an exhaustive classification of causal systems. Among them are the 'self-steering' and 'self-regulating' systems, which together form the class of purposive systems, on whose specific properties the book then focuses. These properties are the mathematical-dynamical foundations of the behavioural and social sciences. This is the definitive book on causality and purposive processes by the originator of the mathematical concept of self-steering.

Computational Methods and Production Engineering

  • 1st Edition
  • May 25, 2017
  • J. Paulo Davim + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 8 5 7 0 9 - 4 8 1 - 0
  • eBook
    9 7 8 - 0 - 8 5 7 0 9 - 4 8 2 - 7
Computational Methods and Production Engineering: Research and Development is an original book publishing refereed, high quality articles with a special emphasis on research and development in production engineering and production organization for modern industry. Innovation and the relationship between computational methods and production engineering are presented. Contents include: Finite Element method (FEM) modeling/simulation; Artificial neural networks (ANNs); Genetic algorithms; Evolutionary computation; Fuzzy logic; neuro-fuzzy systems; Particle swarm optimization (PSO); Tabu search and simulation annealing; and optimization techniques for complex systems. As computational methods currently have several applications, including modeling manufacturing processes, monitoring and control, parameters optimization and computer-aided process planning, this book is an ideal resource for practitioners.

Exterior Algebras

  • 1st Edition
  • May 23, 2017
  • Vincent Pavan
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 2 3 7 - 3
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 2 3 4 8 - 8
Exterior Algebras: Elementary Tribute to Grassmann's Ideas provides the theoretical basis for exterior computations. It first addresses the important question of constructing (pseudo)-Euclidian Grassmmann's algebras. Then, it shows how the latter can be used to treat a few basic, though significant, questions of linear algebra, such as co-linearity, determinant calculus, linear systems analyzing, volumes computations, invariant endomorphism considerations, skew-symmetric operator studies and decompositions, and Hodge conjugation, amongst others.

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Abstract harmonic analysis

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Category theory homological algebra

Commutative rings and algebras

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Field theory and polynomials

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Functions of a complex variable

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Group theory and generalizations

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