Fr. 83.00

Linear Algebra with Python - Theory and Applications

English · Paperback / Softback

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Description

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This textbook is for those who want to learn linear algebra from the basics. After a brief mathematical introduction, it provides the standard curriculum of linear algebra based on an abstract linear space. It covers, among other aspects: linear mappings and their matrix representations, basis, and dimension; matrix invariants, inner products, and norms; eigenvalues and eigenvectors; and Jordan normal forms. Detailed and self-contained proofs as well as descriptions are given for all theorems, formulas, and algorithms.
A unified overview of linear structures is presented by developing linear algebra from the perspective of functional analysis. Advanced topics such as function space are taken up, along with Fourier analysis, the Perron-Frobenius theorem, linear differential equations, the state transition matrix and the generalized inverse matrix, singular value decomposition, tensor products, and linear regression models. These all provide a bridge to more specialized theories based on linear algebra in mathematics, physics, engineering, economics, and social sciences.
Python is used throughout the book to explain linear algebra. Learning with Python interactively, readers will naturally become accustomed to Python coding.  By using Python's libraries NumPy, Matplotlib, VPython, and SymPy,  readers can easily perform large-scale matrix calculations, visualization of calculation results, and symbolic computations.  All the codes in this book can be executed on both Windows and macOS and also on Raspberry Pi.

List of contents

Mathematics and Python.- Linear Spaces and Linear Mappings.- Basis and Dimension.- Matrices.- Elementary Operations and Matrix Invariants.- Inner Product and Fourier Expansion.- Eigenvalues and Eigenvectors.- Jordan Normal Form and Spectrum.- Dynamical Systems.- Applications and Development of Linear Algebra.

About the author










Makoto Tsukada has been studied in the field of functional analysis. He has been teaching linear algebra, analysis, and probability theory for many years. Also, he has taught programming language courses using Pascal, Prolog, C, Python, etc. Yuji Kobayashi, Hiroshi Kaneko, Sin-Ei Takahasi, Kiyoshi Shirayanagi, and Masato Noguchi are specialists in algebra, analysis, statistics, and computers.


Product details

Authors Hiroshi Kaneko, Yuji Kobayashi, Masato Noguchi, Kiyoshi Shirayanagi, Sin-Ei Takahasi, Makoto Tsukada
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 07.12.2024
 
EAN 9789819929535
ISBN 978-981-9929-53-5
No. of pages 309
Dimensions 178 mm x 17 mm x 254 mm
Weight 612 g
Illustrations XV, 309 p. 91 illus., 64 illus. in color.
Series Springer Undergraduate Texts in Mathematics and Technology
Subject Natural sciences, medicine, IT, technology > Mathematics > Arithmetic, algebra

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