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Results 201-210 of 214 (Search time: 0.077 seconds).
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  • Sách/Book

  • Introduction to variational calculus : applications in image processing

    • Authors: Hebert Montegranario (2025)

  • This textbook introduces variational calculus and regularization methods for inverse problems, seamlessly blending classical concepts with contemporary computational applications, particularly in the field of image processing. The classical perspective draws upon foundational topics explored by pioneers such as Euler and Lagrange, establishing a solid theoretical groundwork.
  • Sách/Book

  • Financial Mathematics : Exercises and Solutions

    • Authors: Peter Brusov (2025)

  • This textbook is designed to facilitate a thorough learning for students of financial mathematics. It includes exercises and theoretical questions across seven chapters: Interest Theory, Financial Flows and Annuities, Profitability and Risk of Financial Operations, Portfolio Analysis, Bonds, Modigliani-Miller Theory, and Brusov-Filatova-Orekhova Theory.
  • Sách/Book

  • Exploring linear algebra : labs and projects with mathematica

    • Authors: Crista Arangala (2025)

  • This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition and connections to differential equations
  • Sách/Book

  • Math for programming : learn the math, write better code

    • Authors: Ronald T. Kneusel (2024)

  • In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms
  • Sách/Book

  • A beginner's guide to mathematical proof

    • Authors: Mark J. DeBonis. (2025)

  • A Beginner's Guide to Mathematical Proof prepares mathematics majors for the transition to abstract mathematics, as well as introducing a wider readership of quantitative science students, such as engineers, to the mathematical structures underlying more applied topics
  • Sách/Book

  • Functional analysis for the applied mathematician

    • Authors: Todd Arbogast (2025)

  • This is a self-contained volume providing a rigorous introduction to functional analysis and its applications. Students from mathematics, science, engineering, and certain social science and interdisciplinary programs will benefit from the material. It is accessible to graduate and advanced undergraduate students with a solid background in undergraduate mathematics and an appreciation of mathematical rigor.
  • Sách/Book

  • Optimization, Discrete Mathematics and Applications to Data Sciences

    • Authors: Ashkan Nikeghbali (2025)

  • This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.
  • Sách/Book

  • An introduction to applied numerical analysis

    • Authors: M. A. Hooshyar (2025)

  • This book is based on lecture notes for a numerical analysis course designed mainly for senior undergraduate students majoring in mathematics, engineering, computer science and physical sciences. The book has two overarching goals.