May 1, 2024
Updated May 10, 2025
17 minute read
Interpolation is a fundamental concept in mathematics and various applied sciences, referring to the process of estimating unknown values that fall between known data points. Imagine you have a set of specific temperature readings throughout a day, but you want to know the temperature at a time for which you don't have a direct measurement. Interpolation provides a way to make an educated guess for that missing value based on the surrounding known temperatures. This technique is widely used in fields ranging from engineering and computer science to finance and data analysis to fill in gaps, smooth data, or make predictions within the range of observed data.
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Reading list
We've selected 28 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Interpolation.
This comprehensive reference book covers a wide range of numerical methods, including interpolation, and provides detailed explanations and practical examples. It is highly regarded for its clarity and depth of coverage.
This classic text provides a thorough introduction to interpolation theory and its applications in various fields. It covers both theoretical foundations and practical aspects of interpolation.
In French provides a comprehensive treatment of interpolation and approximation theory, with a focus on functional analysis and complex analysis. It is suitable for advanced students and researchers in the field.
Provides a theoretical treatment of interpolation and approximation using rational functions, with a focus on convergence and stability issues. It is suitable for advanced students and researchers in numerical analysis.
By a renowned expert in numerical analysis provides a modern treatment of approximation theory, including interpolation. It covers both theoretical and computational aspects with a focus on practical applications.
This modern textbook covers standard numerical analysis topics, including interpolation, with an emphasis on fundamental concepts such as convergence, complexity, and conditioning. Its recent publication date means it may include more contemporary perspectives and computational approaches. It suitable textbook for undergraduate courses and provides a solid understanding of the subject.
Covers the theory and application of splines in interpolation and approximation. It provides a comprehensive treatment of the topic, including both theoretical foundations and practical algorithms.
This crucial reference for understanding the practical aspects of implementing numerical algorithms and the impact of finite-precision arithmetic. While not solely about interpolation, the principles of accuracy and stability discussed are directly applicable to interpolation methods and essential for anyone implementing or analyzing them. It valuable resource for graduate students, researchers, and practitioners.
This comprehensive and rigorous classic provides an in-depth treatment of numerical analysis, with detailed coverage of interpolation and approximation. It is suitable for graduate students and researchers due to its theoretical depth and broad scope. It valuable reference for advanced topics and analysis of numerical algorithms.
Focuses on multivariate interpolation and approximation, providing a theoretical framework and practical algorithms for handling data in multiple dimensions. It is suitable for researchers and graduate students in the field.
In German provides a thorough analysis of error estimation for interpolation methods. It covers various types of interpolation and their error bounds, making it suitable for researchers and advanced students in numerical analysis.
Offers a broad introduction to numerical mathematics and computing, covering various topics including interpolation. It balances theoretical concepts with computational aspects, making it suitable for both mathematics and computer science students. It serves as a valuable textbook for understanding the principles behind numerical algorithms and their implementation.
This classic and comprehensive text provides a detailed treatment of numerical methods, including extensive coverage of interpolation and approximation. While older, its depth and rigor make it a valuable reference for graduate students and researchers seeking a thorough understanding of the subject's foundations. It is considered a foundational text in the field.
Focuses specifically on the theoretical foundations of interpolation and approximation. It provides a rigorous mathematical treatment of the subject, exploring various methods and their properties. It is an excellent resource for graduate students and researchers looking to deepen their theoretical understanding of interpolation.
This undergraduate textbook covers a range of numerical methods, including interpolation, with a clear and accessible writing style. It is suitable for students with a background in calculus and linear algebra.
Delves into the theoretical underpinnings of numerical analysis, emphasizing the mathematical principles and analysis of algorithms. It covers topics such as error analysis and stability, which are crucial for a deep understanding of interpolation methods and their limitations. It is best suited for graduate students and researchers with a strong mathematical background.
This textbook provides a solid introduction to numerical methods and their analysis, including a good treatment of interpolation. It is suitable for undergraduate students and offers a balanced approach between theory and practical application. It serves as a good foundation for understanding the core concepts of numerical analysis.
This text covers a wide range of approximation methods, with a significant focus on polynomial and spline interpolation. It provides a solid introduction to the theoretical aspects and practical algorithms. It is suitable for advanced undergraduate or graduate students and serves as a good reference for various approximation techniques.
Focuses specifically on Radial Basis Functions (RBFs), a powerful and contemporary method for multivariate interpolation and approximation, particularly useful for scattered data. It covers both the theoretical aspects and practical implementations. It key resource for researchers and professionals working with modern interpolation techniques.
As the title suggests, this book aims to provide an accessible introduction to numerical analysis. It covers core topics like interpolation in a clear and easy-to-understand manner with numerous examples. is particularly useful for students who are new to the subject or those from engineering and science backgrounds looking for a less abstract approach.
Provides an intuitive and accessible explanation of digital signal processing concepts. It covers practical aspects of DSP, including resampling and interpolation of digital signals, with clear explanations and graphical examples. It is an excellent resource for engineers and others seeking a practical understanding of DSP without excessive mathematical rigor.
Covers fundamental numerical methods with a modern perspective. It includes explanations of interpolation techniques and their applications. It is suitable for undergraduate students in various scientific and engineering fields and provides a good introduction to the computational aspects of numerical analysis.
Explores advanced topics in spline theory and introduces wavelets, another important area in approximation theory with connections to interpolation. It is suitable for graduate students and researchers interested in more advanced mathematical aspects of approximation and their related fields.
Presents a broad overview of numerical methods used across various scientific and engineering disciplines. Interpolation is covered as a key tool within this wider context of scientific computing. It helps readers understand the relevance of interpolation in solving complex problems and valuable reference for professionals in computational fields.
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