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This open-access book connects standard imaging and neuroscience technologies with the numerical solution of PDEs for brain modeling.
This book develops three alternatives for the overall geometry of the universe: hyperbolic, elliptic, and Euclidean geometry.
These notes are intended to give graduate students who have some background in differential geometry, de Rham theory, and classical Lie groups a quick introduction to symplectic geometry.
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A fresh perspective on the world can be found in fractal geometry. Natural patterns that we were not aware of but could easily identify after just one hour of training were all around us.
The fundamentals of using finite difference techniques to solve partial differential equations are covered in this straightforward book.
The well-received book's second edition has undergone considerable revisions, and all of the code is now written in Python version 3.6. (no longer version 2.7).
Based on the well-liked FEniCS software library, this book provides a succinct and gentle introduction to finite element programming in Python.
In this book, computer programming is emphasized as a crucial strategy for resolving mathematical issues. The book is available in two versions: one for Python and one for MATLAB.
In order to solve mathematical issues using MATLAB and Octave, this book emphasizes computer programming as a crucial technique.
Numerous applications of differential geometry can be found in fields like physics and gravitation, for example.