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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

    • Computer-Aided Diagnosis (CAD) Tools and Applications for 3D Medical Imaging

      • 1st Edition
      • Volume 136
      • January 20, 2025
      • English
      • Hardback
        9 7 8 0 3 2 3 9 8 8 5 7 5
      • eBook
        9 7 8 0 3 2 3 9 8 8 5 8 2
      Computer-Aided Diagnosis (CAD) Tools and Applications for 3D Medical Imaging, Volume 136 in the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. Chapters in this updated release include Introduction to Computer-aided diagnosis (CAD) tools and applications, Enhancement of three-dimensional medical images, Machine Learning Based Techniques for Computer Aided Diagnosis, AI-based image processing techniques for the automatic segmentation of human organs, Watermarking over medical images, Compressive Sensing for 3D Medical Image Compression, and more.Additional chapters cover Image encryption of medical images, Image Registration for 3D Medical Images, Texture-based computations for processing volumetric dental image, Language Processing in the Brain :an fMRI Study, Research challenges and emerging futuristic evolution for 3D medical image processing, Software based medical image analysis, and Automated 3D Visualization and Volume Estimation of Hepatic Structures for Treatment Planning of Hepatocellular Carcinoma.

    • Role of Internet of Things and Machine Learning in Smart Healthcare

      • 1st Edition
      • Volume 137
      • February 1, 2025
      • English
      • Hardback
        9 7 8 0 4 4 3 2 2 3 8 6 0
      • eBook
        9 7 8 0 4 4 3 2 2 3 8 7 7
      Role of Internet of Things and Machine Learning in Smart Healthcare, Volume 137 of the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. Published since 1960, this series provides contributors with a medium to explore their subjects in greater depth and breadth than typical journal articles. Additionally, the book discusses the basic concepts of the Internet of Things (IoT) and Machine Learning (ML), along with their various applications in smart healthcare. It proposes novel techniques by integrating IoT, cloud computing, and ML algorithms to efficiently manage e-healthcare data and improve security. The volume also addresses research challenges and probable future directions in smart healthcare using IoT and ML, making it a comprehensive resource for researchers, practitioners, and students interested in advancing healthcare technologies.

    • Machine Learning Solutions for Inverse Problems: Part A

      • 1st Edition
      • Volume 26
      • October 1, 2025
      • English
      • Hardback
        9 7 8 0 4 4 3 4 1 7 8 9 4
      • eBook
        9 7 8 0 4 4 3 4 1 7 9 0 0
      Machine Learning Solutions for Inverse Problems: Part A, Volume 26 in the Handbook of Numerical Analysis, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Data-Driven Approaches for Generalized Lasso Problems, Implicit Regularization of the Deep Inverse Prior via (Inertial) Gradient Flow, Generalized Hardness of Approximation, Hallucinations, and Trustworthiness in Machine Learning for Inverse Problems, Energy-Based Models for Inverse Imaging Problems, Regularization Theory of Stochastic Iterative Methods for Solving Inverse Problems, and more.Other sections cover Advances in Identifying Differential Equations from Noisy Data Observations, The Complete Electrode Model for Electrical Impedance Tomography: A Comparative Study of Deep Learning and Analytical Methods, Learned Iterative Schemes: Neural Network Architectures for Operator Learning, Jacobian-Free Backpropagation for Unfolded Schemes with Convergence Guarantees, and Operator Learning Meets Inverse Problems: A Probabilistic Perspective

    • Quaternion Generalized Inverses

      • 1st Edition
      • July 9, 2025
      • Ivan I. Kyrchei
      • English
      • Paperback
        9 7 8 0 4 4 3 3 4 1 4 5 8
      • eBook
        9 7 8 0 4 4 3 3 4 1 4 6 5
      A cornerstone of linear algebra, the determinant's utility in real and complex fields is undeniable, though traditionally limited to invertibility, rank, and solving linear systems. Quaternion Generalized Inverses: Foundations, Theory, Problems, and Solutions ventures into uncharted territory: extending these concepts to linear algebra over the noncommutative quaternion skew field. The author's groundbreaking theory of "noncommutative" row–column determinants is central to this exploration, a significant advancement beyond the Moore determinant. This seven-chapter work thoroughly introduces the history of noncommutative determinants before delving into the author's theory and its application to inverse matrix computation and Cramer's rule for quaternion systems. The main portion of this work is dedicated to a comprehensive examination of quaternion generalized inverses, spanning the well-established Moore–Penrose and Drazin inverses to more recent developments such as core-EP and composite inverses. The book provides their definitions, properties, and, uniquely, their determinantal representations based on the author's noncommutative determinants. It culminates in demonstrating their powerful applications in solving a wide range of quaternion matrix equations, including Sylvester-type and constrained equations, as well as differential matrix equations.

    • Stochastic Theory of Service Systems

      • 1st Edition
      • May 23, 2025
      • L. Kosten
      • I. N. Sneddon + 1 more
      • English
      • Paperback
        9 7 8 1 4 8 3 1 1 8 1 6 1
      • eBook
        9 7 8 1 4 8 3 1 5 0 5 8 1
      International Series of Monographs in Pure and Applied Mathematics, Volume 103: Stochastic Theory of Service Systems focuses on the principles, methodologies, and approaches involved in the stochastic theory of service systems. The publication first examines the general description of service systems, characteristics of the arrival process, standard cases, and the distribution of waiting-times in the system M/M/c-delay. Discussions focus on "random" condition, probability of delay and average waiting-time for the system M/M/c-delay, Engset formula, and probability of blocking for the system M/M/c-blocking. The text then examines general holding-time assumption, non-stationary behavior, and priority. Topics include pre-emptive priority, transient behavior of the system M/G/1-delay, Markov process with a finite number of states, and hyperexponential distributions. The manuscript takes a look at simulation, arrival and service in batches, and restricted availability, including approximate determination of probabilities of blocking, "unscheduled ferry problem", principles of roulette simulation, and implementation of randomness. The publication is a dependable source material for researchers interested in the stochastic theory of service systems.

    • Approximation Theory and Applications

      • 1st Edition
      • February 4, 2025
      • Sergei Aliukov
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 1 4 1 8
      • eBook
        9 7 8 0 4 4 3 2 9 1 4 2 5
      Approximation Theory and Applications: Piecewise Linear and Generalized Functions presents the main provisions of approximation theory, and considers existing and new methods for approximating piecewise linear and generalized functions, widely used to solve problems related to mathematical modeling of systems, processes, and phenomena in fields ranging from engineering to economics. The widespread use of piecewise linear and generalized functions is explained by the simplicity of their structure. However, challenges often arise when constructing solutions over the entire domain of these functions, requiring the use special mathematical methods to put theory into practice. This book first offers a first full foundation in approximation theory as it relates to piecewise linear and generalized functions, followed by staged methods to resolve common problems in practice, with applications examined across structural mechanics, medicine, quantum theory, signal theory, semiconductor theory, mechanical engineering, heat engineering, and other fields. Later chapters consider numerical verification of approximation methods, and approximation theory as the basis for new macroeconomic theory with impulse and jump characteristics. Each chapter includes questions for review and sample problems, accompanied by a separate Solutions Manual hosted for instructor access.

    • Irreducible Tensorial Sets

      • 1st Edition
      • February 3, 2025
      • U. Fano + 1 more
      • H. S. W. Massey + 1 more
      • English
      • Paperback
        9 7 8 1 4 8 3 2 5 3 8 4 8
      • eBook
        9 7 8 1 4 8 3 2 7 6 1 6 8
      Irreducible Tensorial Sets discusses mathematical methods originating from the theory of coupling and recoupling of angular momenta in atomic physics that constitute an extension of vector and tensor algebra. The book presents a unified treatment with a compact system of notations from different approaches, such as group theory, algebra, and quantum mechanical transformation theory. It discusses irreducible tensorial sets that cover different sets of quantities such as tensor components and states of atomic systems. It also explains quantum mechanical applications, coupling and recoupling of atomic and nuclear states, the Wigner-Eckart theorem, and the products of tensorial sets of operators. The text shows how to calculate the interaction energy between atomic systems couple with one another with a constant total angular momentum. The book also explains the correlations which are functions of the Euler angles between the frame of reference in which a radiation is observed and a frame of reference attached to the orienting radiation or field. It then cites sample problems related to the angular distribution of radiations. The book will prove useful for physicists, for mathematicians, or for readers with some knowledge in theoretical physics, particularly on theory of groups and quantum mechanics.

    • Finite Mathematics

      • 1st Edition
      • April 24, 2025
      • Andrew McHugh
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 0 9 4 7
      • eBook
        9 7 8 0 4 4 3 2 9 0 9 5 4
      Finite Mathematics: An Introduction with Applications in Business, Social Sciences, and Music presents core concepts of finite mathematics in a clear, intuitive fashion designed to reinforce understanding. The book begins with finite mathematics foundations, with explanations and exercises on combinatorics, logic, set theory, sequences and series, functions and functional notation, elementary probability, linear programming and systems, and Markov chains. Later chapters explore and explain a range of finite mathematics applications, from game theory to voting, apportionment, finance, graph theory, and the science and physics of music.Written with an accessible, example-based approach, this book engages STEM and non-STEM students alike, preparing them for courses across a range of quantitative fields, social sciences, and the liberal arts. Problem-solving exercises are featured at the conclusion of each subsection, with corresponding answers in the appendix. The book is also accompanied by a solutions manual, sample projects assignments, tests, lecture slides, and datasets on a companion website.

    • Agent-Based Models with MATLAB

      • 1st Edition
      • January 20, 2025
      • Erik Cuevas + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 0 0 4 1
      • eBook
        9 7 8 0 4 4 3 2 4 0 0 5 8
      Agent-Based Models with MATLAB introduces Agent-Based Modeling (ABM), one of the most important methodologies for complex systems modeling. The book explores computational implementations and accompanying MATLAB software code as a means of inspiring readers to apply agent-based models to solve a diverse range of problems. It comes with a large amount of software code that accompanies the main text, and the modeling systems described in the book are implemented using MATLAB as the programming language. Despite the heavy mathematical components of Agent-Based Models and complex systems, it is possible to utilize these models without in-depth understanding of their mathematical fundamentals.This book enables computer scientists, mathematicians, researchers, and engineers to apply ABM in a wide range of research and engineering applications. It gradually advances from basic to more advanced methods while reinforcing complex systems through practical, hands-on applications of various computational models.

    • Mathematical Modeling in Bioscience

      • 1st Edition
      • March 27, 2025
      • Hemen Dutta
      • English
      • Paperback
        9 7 8 0 4 4 3 1 5 4 4 5 4
      • eBook
        9 7 8 0 4 4 3 1 5 4 4 6 1
      Mathematical Modeling in Bioscience: Theory and Applications provides readers with tools and techniques for mathematical modeling in bioscience through a wide range of novel and intriguing topics. The book concentrates on larger elements of mathematical modeling in bioscience, including topics such as modeling of the Topp--Leone new power generalized Weibull-G distribution family, vector-borne disease modeling, transmission modeling of SARS-COV-2 among other infectious diseases, pattern formulation models, compartmental models for HIV/AIDS transmission, population models, irrigation scheduling models, and predator--prey models. The readers will discover a variety of new methods, approaches, and techniques, as well as a wide range of applications demonstrating key concepts in bioscience modeling. This book provides a leading-edge resource for researchers in a variety of scientific fields who are interested in mathematical modeling, including mathematics, statistics, biology, biomedical engineering, computer science, and applied sciences.

Related subjects

Mathematics and applied mathematics

Statistics and probability