Computational Methods Using Matlab Hb
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Computational Methods Using Matlab? Hb
Author: THIRUVIKRAMAN
language: en
Publisher: IOP Publishing Limited
Release Date: 2022-03-31
This book provides an introduction to the computational methods commonly employed by physicists and engineers. The book discusses the details of the numerical algorithms involved and also provides MATLAB code for their implementation. Applications of numerical methods to various physical systems including nonlinear systems and fractals are also discussed. Each chapter has a number of solved examples and end of chapter exercises. Solutions to most of the exercises have also been included. The book is suitable for undergraduates in physics or engineering. The methods discussed and some of the examples will also be useful for other scientists and engineers who wish to learn the basics of computational/ numerical methods for solving problems. Key Features: Comprehensive coverage of basic theory Accompanying MATLAB programs Applications of computational methods to various areas of physics Worked examples and end of chapter problems Enhanced with animation and sound files
Numerical Techniques in MATLAB
In this book, various numerical methods are discussed in a comprehensive way. It delivers a mixture of theory, examples and MATLAB® practicing exercises to help the students in improving their skills. To understand the MATLAB programming in a friendly style, the examples are solved. The MATLAB codes are mentioned in the end of each topic. Throughout the text, a balance between theory, examples and programming is maintained. Key Features Methods are explained with examples and codes System of equations has given full consideration Use of MATLAB is learnt for every method This book is suitable for graduate students in mathematics, computer science and engineering.
Kernel-based Approximation Methods Using Matlab
Author: Gregory E Fasshauer
language: en
Publisher: World Scientific Publishing Company
Release Date: 2015-07-30
In an attempt to introduce application scientists and graduate students to the exciting topic of positive definite kernels and radial basis functions, this book presents modern theoretical results on kernel-based approximation methods and demonstrates their implementation in various settings. The authors explore the historical context of this fascinating topic and explain recent advances as strategies to address long-standing problems. Examples are drawn from fields as diverse as function approximation, spatial statistics, boundary value problems, machine learning, surrogate modeling and finance. Researchers from those and other fields can recreate the results within using the documented MATLAB code, also available through the online library. This combination of a strong theoretical foundation and accessible experimentation empowers readers to use positive definite kernels on their own problems of interest.