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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.

    • Reliability Analysis and Plans for Successive Testing

      • 1st Edition
      • January 15, 2021
      • Narayanaswamy Balakrishnan + 2 more
      • English
      • Hardback
        9 7 8 0 1 2 8 0 4 2 8 8 5
      • eBook
        9 7 8 0 1 2 8 0 4 3 6 2 2
      Reliability Analysis and Plans for Successive Testing: Start-up Demonstration Tests and Applications discusses all past and recent developments on start-up demonstration tests in the context of current numerical and illustrative examples to clarify available methods for distribution theorists and applied mathematicians dealing with control problems. Throughout the book, the authors focus on the panorama of open problems and issues of further interest. As contemporary manufacturers face tremendous commercial pressures to assemble works of high reliability, defined as ‘the probability of the product performing its role under the stated conditions and over a specified period of time’, this book helps address testing issues.
    • Data Science: Theory and Applications

      • 1st Edition
      • Volume 44
      • February 12, 2021
      • English
      • Hardback
        9 7 8 0 3 2 3 8 5 2 0 0 5
      • eBook
        9 7 8 0 3 2 3 8 5 2 0 1 2
      Data Science: Theory and Applications, Volume 44 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of interesting topics, including Modeling extreme climatic events using the generalized extreme value distribution, Bayesian Methods in Data Science, Mathematical Modeling in Health Economic Evaluations, Data Science in Cancer Genomics, Blockchain Technology: Theory and Practice, Statistical outline of animal home ranges, an application of set estimation, Application of Data Handling Techniques to Predict Pavement Performance, Analysis of individual treatment effects for enhanced inferences in medicine, and more. Additional sections cover Nonparametric Data Science: Testing Hypotheses in Large Complex Data, From Urban Mobility Problems to Data Science Solutions, and Data Structures and Artificial Intelligence Methods.
    • Sabermetrics

      • 1st Edition
      • October 27, 2021
      • Gabriel B. Costa
      • English
      • Paperback
        9 7 8 0 1 2 8 2 2 3 4 5 1
      • eBook
        9 7 8 0 1 2 8 2 2 3 4 6 8
      Sabermetrics: Baseball, Steroids, and How the Game has Changed Over the Past Two Generations offers an introduction to this increasing area of interest to statisticians, students of the game, and many others. Pairing a primer on the applied math with an overview of the origin of the field and its context within baseball today, the work provides an engaging resource for students and interested readers. It includes coverage of relevant baseball history, Bill James and SABR, broken records and steroids. Drawing on the author’s experience teaching the subject at Seton Hall University since 1988, Sabermetrics also offers practice questions and solutions for class use.
    • Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

      • 1st Edition
      • Volume 122
      • March 28, 2021
      • 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.
    • An Introduction to Hypergeometric, Supertrigonometric, and Superhyperbolic Functions

      • 1st Edition
      • January 23, 2021
      • Xiao-Jun Yang
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 1 5 4 7
      • 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.
    • 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.
    • Statistical Methods

      • 4th Edition
      • April 16, 2021
      • Donna L. Mohr + 2 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 0 4 3 5
      • eBook
        9 7 8 0 3 2 3 8 9 9 8 8 8
      Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results.
    • AI and Cloud Computing

      • 1st Edition
      • Volume 120
      • January 13, 2021
      • English
      • Hardback
        9 7 8 0 1 2 8 2 1 1 4 7 2
      • eBook
        9 7 8 0 1 2 8 2 1 1 4 8 9
      AI and Cloud Computing, Volume 120 in the Advances in Computers series, highlights new advances in the field, with this updated volume presenting interesting chapters on topics including A Deep-forest based Approach for Detecting Fraudulent Online Transaction, Design of Cyber-Physical-Socia... Systems with Forensic-awareness Based on Deep Learning, Review on Privacy-preserving Data Comparison Protocols in Cloud Computing, Fingerprint Liveness Detection Using an Improved CNN with the Spatial Pyramid Pooling Structure, Protecting Personal Sensitive Data Security in the Cloud with Blockchain, and more.
    • Introduction to Robust Estimation and Hypothesis Testing

      • 5th Edition
      • September 18, 2021
      • Rand R. Wilcox
      • English
      • Paperback
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      • eBook
        9 7 8 0 1 2 8 2 0 0 9 9 5
      Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful ‘how-to’ on the application of robust methods utilizing easy-to-use software. This trusted resource provides an overview of modern robust methods, including improved techniques for dealing with outliers, skewed distribution curvature, and heteroscedasticity that can provide substantial gains in power. Coverage includes techniques for comparing groups and measuring effect size, current methods for comparing quantiles, and expanded regression methods for both parametric and nonparametric techniques. The practical importance of these varied methods is illustrated using data from real world studies. Over 1700 R functions are included to support comprehension and practice.
    • Geometric Partial Differential Equations - Part 2

      • 1st Edition
      • Volume 22
      • January 26, 2021
      • Andrea Bonito + 1 more
      • English
      • Hardback
        9 7 8 0 4 4 4 6 4 3 0 5 6
      • eBook
        9 7 8 0 4 4 4 6 4 3 0 6 3
      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.