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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.

BooksJournals

    • Algebraic Theory for True Concurrency

      • 1st Edition
      • January 3, 2023
      • Yong Wang
      • English
      • Paperback
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      • eBook
        9 7 8 0 4 4 3 1 8 9 1 3 5
      Algebraic Theory for True Concurrency presents readers with the algebraic laws for true concurrency. Parallelism and concurrency are two of the core concepts within computer science. This book covers the different realms of concurrency, which enables programs, algorithms or problems to be broken out into order-independent or partially ordered components to improve computation and execution speed. There are two primary approaches for executing concurrency: interleaving concurrency and true concurrency. The main representative of interleaving concurrency is bisimulation/rooted branching bisimulation equivalences which is also readily explored. This work eventually founded the comprehensive axiomatization modulo bisimulation equivalence -- ACP (Algebra of Communicating Processes).The other approach to concurrency is true concurrency. Research on true concurrency is active and includes many emerging applications. First, there are several truly concurrent bisimulation equivalences, including: pomset bisimulation equivalence, step bisimulation equivalence, history-preserving (hp-) bisimulation equivalence, and hereditary history-preserving (hhp-) bisimulation equivalence, the most well-known truly concurrent bisimulation equivalence.

    • Boolean Systems

      • 1st Edition
      • January 6, 2023
      • Serban E. Vlad
      • English
      • Paperback
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      • eBook
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      The Boolean functions may be iterated either asynchronously, when their coordinates are computed independently of each other, or synchronously, when their coordinates are computed at the same time. In Boolean Systems: Topics in Asynchronicity, a book addressed to mathematicians and computer scientists interested in Boolean systems and their use in modelling, author Serban E. Vlad presents a consistent and original mathematical theory of the discrete-time Boolean asynchronous systems. The purpose of the book is to set forth the concepts of such a theory, resulting from the synchronous Boolean system theory and mostly from the synchronous real system theory, by analogy, and to indicate the way in which known synchronous deterministic concepts generate new asynchronous nondeterministic concepts. The reader will be introduced to the dependence on the initial conditions, periodicity, path-connectedness, topological transitivity, and chaos. A property of major importance is invariance, which is present in five versions. In relation to it, the reader will study the maximal invariant subsets, the minimal invariant supersets, the minimal invariant subsets, connectedness, separation, the basins of attraction, and attractors. The stability of the systems and their time-reversal symmetry end the topics that refer to the systems without input. The rest of the book is concerned with input systems. The most consistent chapters of this part of the book refer to the fundamental operating mode and to the combinational systems (systems without feedback). The chapter Wires, Gates, and Flip-Flops presents a variety of applications. The first appendix addresses the issue of continuous time, and the second one sketches the important theory of Daizhan Cheng, which is put in relation to asynchronicity. The third appendix is a bridge between asynchronicity and the symbolic dynamics of Douglas Lind and Brian Marcus.

    • Introductory Differential Equations

      • 6th Edition
      • December 21, 2023
      • Martha L. Abell + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 6 0 5 8 5
      • eBook
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      **2025 Textbook and Academic Authors Association (TAA) McGuffey Longevity Award Winner**Introductory Differential Equations, Sixth Edition provides the foundations to assist students in learning not only how to read and understand differential equations, but also how to read technical material in more advanced texts as they progress through their studies. The book's accessible explanations and many robust sample problems are appropriate for a first semester course in introductory ordinary differential equations (including Laplace transforms), for a second course in Fourier series and boundary value problems, and for students with no background on the subject.

    • Fundamentals of Data Science

      • 1st Edition
      • November 17, 2023
      • Jugal K. Kalita + 2 more
      • English
      • Paperback
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      • eBook
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      Fundamentals of Data Science: Theory and Practice presents basic and advanced concepts in data science along with real-life applications. The book provides students, researchers and professionals at different levels a good understanding of the concepts of data science, machine learning, data mining and analytics. Users will find the authors’ research experiences and achievements in data science applications, along with in-depth discussions on topics that are essential for data science projects, including pre-processing, that is carried out before applying predictive and descriptive data analysis tasks and proximity measures for numeric, categorical and mixed-type data. The book's authors include a systematic presentation of many predictive and descriptive learning algorithms, including recent developments that have successfully handled large datasets with high accuracy. In addition, a number of descriptive learning tasks are included.

    • Probability and Statistics for Physical Sciences

      • 2nd Edition
      • September 5, 2023
      • Brian Martin + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 8 9 6 9 2
      • eBook
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      Probability and Statistics for Physical Sciences, Second Edition is an accessible guide to commonly used concepts and methods in statistical analysis used in the physical sciences. This brief yet systematic introduction explains the origin of key techniques, providing mathematical background and useful formulas. The text does not assume any background in statistics and is appropriate for a wide-variety of readers, from first-year undergraduate students to working scientists across many disciplines.

    • Deep Learning

      • 1st Edition
      • Volume 48
      • February 28, 2023
      • English
      • Hardback
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      • eBook
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      Deep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Generative Adversarial Networks for Biometric Synthesis, Data Science and Pattern Recognition, Facial Data Analysis, Deep Learning in Electronics, Pattern Recognition, Computer Vision and Image Processing, Mechanical Systems, Crop Technology and Weather, Manipulating Faces for Identity Theft via Morphing and Deepfake, Biomedical Engineering, and more.

    • Advances in Computers

      • 1st Edition
      • Volume 130
      • March 1, 2023
      • Ali Hurson
      • English
      • Hardback
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      • eBook
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      The 130th volume is an eclectic volume inspired by recent issues of interest in research and development in computer science and computer engineering. The volume is a collection of five chapters.

    • Automata Theory and Formal Languages

      • 1st Edition
      • April 28, 2023
      • Pallavi Vijay Chavan + 1 more
      • English
      • Paperback
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      • eBook
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      Automata Theory and Formal Languages presents the difficult concepts of automata theory in a straightforward manner, including discussions on diverse concepts and tools that play major roles in developing computing machines, algorithms and code. Automata theory includes numerous concepts such as finite automata, regular grammar, formal languages, context free and context sensitive grammar, push down automata, Turing machine, and decidability, which constitute the backbone of computing machines. This book enables readers to gain sufficient knowledge and experience to construct and solve complex machines. Each chapter begins with key concepts followed by a number of important examples that demonstrate the solution. The book explains concepts and simultaneously helps readers develop an understanding of their application with real-world examples, including application of Context Free Grammars in programming languages and Artificial Intelligence, and cellular automata in biomedical problems.

    • Artificial Intelligence

      • 1st Edition
      • Volume 49
      • August 25, 2023
      • English
      • Hardback
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      • eBook
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      Artificial Intelligence, Volume 49 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics. Chapters in this new release include AI Teacher-Student based Adaptive Structural Deep Learning Model and Its Estimating Uncertainty of Image Data, Machine-derived Intelligence: Computations Beyond the Null Hypothesis, Object oriented basis of artificial intelligence methodologies I in Judicial Systems in India, Artificial Intelligence in Systems Biology, Machine-Learning in Geometry and Physics, Innovation and Machine Learning: Crowdsourcing Open-Source Natural Language Processing (NLP) Algorithms to Advance Public Health Surveillance, and more. Other chapters cover Learning and identity testing of Markov chains, Data privacy for machine learning and statistics, and The interface between AI and Mathematics.

    • Numerical Control: Part B

      • 1st Edition
      • Volume 24
      • February 20, 2023
      • Emmanuel Trélat + 1 more
      • English
      • Hardback
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      • eBook
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      Numerical Control: Part B, Volume 24 in the Handbook of Numerical Analysis series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this volume include Control problems in the coefficients and the domain for linear elliptic equations, Computational approaches for extremal geometric eigenvalue problems, Non-overlapping domain decomposition in space and time for PDE-constrained optimal control problems on networks, Feedback Control of Time-dependent Nonlinear PDEs with Applications in Fluid Dynamics, Stabilization of the Navier-Stokes equations - Theoretical and numerical aspects, Reconstruction algorithms based on Carleman estimates, and more. Other sections cover Discrete time formulations as time discretization strategies in data assimilation, Back and forth iterations/Time reversal methods, Unbalanced Optimal Transport: from Theory to Numerics, An ADMM Approach to the Exact and Approximate Controllability of Parabolic Equations, Nonlocal balance laws -- an overview over recent results, Numerics and control of conservation laws, Numerical approaches for simulation and control of superconducting quantum circuits, and much more.

Related subjects

Mathematics and applied mathematics

Statistics and probability