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Books in Mathematics and applied mathematics

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51-60 of 2229 results in All results

Extremal Problems and Inequalities of Markov-Bernstein Type for Algebraic Polynomials

  • 1st Edition
  • February 10, 2022
  • Robert B. Gardner + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 1 9 8 8 - 4
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 2 0 0 7 - 1
Inequalities for polynomials and their derivatives are very important in many areas of mathematics, as well as in other computational and applied sciences; in particular they play a fundamental role in approximation theory. Here, not only Extremal Problems and Inequalities of Markov-Bernstein Type for Algebraic Polynomials, but also ones for trigonometric polynomials and related functions, are treated in an integrated and comprehensive style in different metrics, both on general classes of polynomials and on important restrictive classes of polynomials. Primarily for graduate and PhD students, this book is useful for any researchers exploring problems which require derivative estimates. It is particularly useful for those studying inverse problems in approximation theory.

Advances in Computers

  • 1st Edition
  • Volume 124
  • February 4, 2022
  • Suyel Namasudra
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 8 5 6 8 8 - 1
  • eBook
    9 7 8 - 0 - 3 2 3 - 8 5 6 8 9 - 8
Advances in Computers, Volume 124 presents updates on innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on Traffic-Load-Aware Virtual Channel Power-gating in Network-on-Chips, An Efficient DVS Scheme for On-chip Networks, A Power-Performance Balanced Network-on-Chip for Mixed CPU-GPU Systems, Routerless Networks-on-Chip, Routing Algorithm Design for Power- and Temperature-Aware NoCs, Approximate Communication for Energy-Efficient Network-on-Chip, Power-Efficient NoC Design by Partial Topology Reconfiguration, The Design of a Deflection-based Energy-efficient On-chip Network, and Power-Gating in Networks-on-Chip.

Differential Equations with Mathematica

  • 5th Edition
  • January 18, 2022
  • Martha L. Abell + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 4 1 6 0 - 8
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 8 4 3 6 - 2
Differential Equations with Mathematica, Fifth Edition uses the fundamental concepts of the popular platform to solve (analytically, numerically, and/or graphically) differential equations of interest to students, instructors, and scientists. Mathematica’s diversity makes it particularly well suited to performing calculations encountered when solving many ordinary and partial differential equations. In some cases, Mathematica’s built-in functions can immediately solve a differential equation by providing an explicit, implicit, or numerical solution. In other cases, Mathematica can be used to perform the calculations encountered when solving a differential equation. Because one goal of elementary differential equations courses is to introduce students to basic methods and algorithms so that they gain proficiency in them, nearly every topic covered this book introduces basic commands, also including typical examples of their application. A study of differential equations relies on concepts from calculus and linear algebra, so this text also includes discussions of relevant commands useful in those areas. In many cases, seeing a solution graphically is most meaningful, so the book relies heavily on Mathematica’s outstanding graphics capabilities.

New Numerical Scheme with Newton Polynomial

  • 1st Edition
  • June 10, 2021
  • Abdon Atangana + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 8 5 4 4 8 - 1
  • eBook
    9 7 8 - 0 - 3 2 3 - 8 5 8 0 2 - 1
New Numerical Scheme with Newton Polynomial: Theory, Methods, and Applications provides a detailed discussion on the underpinnings of the theory, methods and real-world applications of this numerical scheme. The book's authors explore how this efficient and accurate numerical scheme is useful for solving partial and ordinary differential equations, as well as systems of ordinary and partial differential equations with different types of integral operators. Content coverage includes the foundational layers of polynomial interpretation, Lagrange interpolation, and Newton interpolation, followed by new schemes for fractional calculus. Final sections include six chapters on the application of numerical scheme to a range of real-world applications. Over the last several decades, many techniques have been suggested to model real-world problems across science, technology and engineering. New analytical methods have been suggested in order to provide exact solutions to real-world problems. Many real-world problems, however, cannot be solved using analytical methods. To handle these problems, researchers need to rely on numerical methods, hence the release of this important resource on the topic at hand.

Advances in Computers

  • 1st Edition
  • Volume 123
  • June 8, 2021
  • Suyel Namasudra
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 2 4 1 2 1 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 4 1 2 2 - 6
Advances in Computers, Volume 123 presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on Downlink Resource Allocations of Satellite-Airborne-Terrestrial Networks Integration, Evaluating Software Testing Techniques: A Systematic Mapping Study, The Screening Phase in Systematic Reviews: Can we speed up the process?, A Survey on Cloud-Based Video Streaming Services, and User Behavior-Ensemble Learning based Improving QoE Fairness in HTTP Adaptive Streaming over SDN approach.

Mathematica by Example

  • 6th Edition
  • June 1, 2021
  • Martha L. Abell + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 4 1 6 3 - 9
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 0 8 1 7 - 7
Mathematica by Example, Sixth Edition is an essential resource for the Mathematica user, providing step-by-step instructions on achieving results from this powerful software tool. The book fully accounts for the changes to functionality and visualization capabilities and accomodates the full array of new extensions in the types of data and problems that Mathematica can immediately handle, including cloud services and systems, geographic and geometric computation, dynamic visualization, interactive applications and other improvements. It is an ideal text for scientific students, researchers, and aspiring programmers seeking further understanding of Mathematica. Written by seasoned practitioners with a view to practical implementation and problem-solving, the book's pedagogy is delivered clearly and without jargon using representative biological, physical and engineering problems. Code is provided on an ancillary website to support the use of Mathematica across diverse applications and subject areas.

Advanced Mathematics for Engineering Students

  • 1st Edition
  • May 20, 2021
  • Brent J. Lewis + 2 more
  • English
  • Paperback
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  • eBook
    9 7 8 - 0 - 1 2 - 8 2 3 6 8 2 - 6
Advanced Mathematics for Engineering Students: The Essential Toolbox provides a concise treatment for applied mathematics. Derived from two semester advanced mathematics courses at the author’s university, the book delivers the mathematical foundation needed in an engineering program of study. Other treatments typically provide a thorough but somewhat complicated presentation where students do not appreciate the application. This book focuses on the development of tools to solve most types of mathematical problems that arise in engineering – a “toolbox” for the engineer. It provides an important foundation but goes one step further and demonstrates the practical use of new technology for applied analysis with commercial software packages (e.g., algebraic, numerical and statistical).

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

  • 1st Edition
  • Volume 122
  • March 28, 2021
  • Shiho Kim + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 2 3 1 2 3 - 4
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 3 1 2 4 - 1
Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into artificial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more.

Geometric Partial Differential Equations - Part 2

  • 1st Edition
  • Volume 22
  • January 26, 2021
  • Andrea Bonito + 1 more
  • English
  • Hardback
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  • eBook
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Besides their intrinsic mathematical interest, geometric partial differential equations (PDEs) are ubiquitous in many scientific, engineering and industrial applications. They represent an intellectual challenge and have received a great deal of attention recently. The purpose of this volume is to provide a missing reference consisting of self-contained and comprehensive presentations. It includes basic ideas, analysis and applications of state-of-the-art fundamental algorithms for the approximation of geometric PDEs together with their impacts in a variety of fields within mathematics, science, and engineering.

An Introduction to Hypergeometric, Supertrigonometric, and Superhyperbolic Functions

  • 1st Edition
  • January 23, 2021
  • Xiao-Jun Yang
  • English
  • Paperback
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  • eBook
    9 7 8 - 0 - 3 2 3 - 8 5 2 8 2 - 1
An Introduction to Hypergeometric, Supertigonometric, and Superhyperbolic Functions gives a basic introduction to the newly established hypergeometric, supertrigonometric, and superhyperbolic functions from the special functions viewpoint. The special functions, such as the Euler Gamma function, the Euler Beta function, the Clausen hypergeometric series, and the Gauss hypergeometric have been successfully applied to describe the real-world phenomena that involve complex behaviors arising in mathematics, physics, chemistry, and engineering.

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