Spectral Methods for Time-Dependent Problems (Cambridge Monographs on Applied and Computational Mathematics)

Spectral Methods for Time-Dependent Prob

📁 Spectral Methods for Time-Dependent Problems: Analysis and Applications

✍ Jan S. Hesthaven, Professor Sigal Gottlieb, David Gottlieb 📂 Library 📅 2007 🏛 Cambridge University Press 🌐 English

Spectral methods are well-suited to solve problems modeled by time-dependent partial differential equations: they are fast, efficient and accurate and widely used by mathematicians and practitioners. This class-tested introduction, the first on the subject, is ideal for graduate courses, or self-stu

Spectral Methods for Time-Dependent Prob

📁 Spectral Methods for Time-Dependent Problems

✍ Jan S. Hesthaven, Sigal Gottlieb, David Gottlieb, 📂 Library 📅 2007 🏛 Cambridge University Press 🌐 English

Spectral methods are well-suited to solve problems modeled by time-dependent partial differential equations: they are fast, efficient and accurate and widely used by mathematicians and practitioners. This class-tested introduction, the first on the subject, is ideal for graduate courses, or self-stu

Spectral methods for time-dependent prob

📁 Spectral methods for time-dependent problems

✍ Hesthaven J.S., Gottlieb S., Gottlieb D. 📂 Library 📅 2007 🏛 CUP 🌐 English

Spectral methods are well-suited to solve problems modeled by time-dependent partial differential equations: they are fast, efficient and accurate and widely used by mathematicians and practitioners. This class-tested introduction, the first on the subject, is ideal for graduate courses, or self-stu

Spectral Methods for Time-Dependent Prob

📁 Spectral Methods for Time-Dependent Problems

✍ Jan S. Hesthaven, Sigal Gottlieb, David Gottlieb 📂 Library 📅 2007 🏛 Cambridge University Press 🌐 English

Spectral Methods for Time-Dependent Prob

📁 Spectral Methods for Time-Dependent Problems

✍ Jan S. Hesthaven, Professor Sigal Gottlieb, David Gottlieb 📂 Library 📅 2007 🏛 Cambridge University Press 🌐 English

I bought this book to help me understand spectral methods enough to employ them for a nonlinear PDE problem that I have been working on. I sure am glad that I did! Here is a very complete and readable account of both the theoretical underpinnings and practical aspects of spectral methods. Spectra

The Christoffel–Darboux Kernel for Data

📁 The Christoffel–Darboux Kernel for Data Analysis (Cambridge Monographs on Applied and Computational Mathematics)

✍ Jean Bernard Lasserre, Edouard Pauwels, Mihai Putinar 📂 Library 📅 2022 🏛 Cambridge University Press 🌐 English

<span>The Christoffel–Darboux kernel, a central object in approximation theory, is shown to have many potential uses in modern data analysis, including applications in machine learning. This is the first book to offer a rapid introduction to the subject, illustrating the surprising effectiveness of