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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.
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.
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.
Gives a unified overview of various phenomena with linear structure from the perspective of functional analysis
Makes it enjoyable to learn linear algebra with Python by performing linear calculations without manual calculations
Handles large data such as images and sound using Python and deepens the understanding of linear structures
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Arithmetik & Algebra |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Seiten: | 324 |
| Reihe: | Springer Undergraduate Texts in Mathematics and Technology |
| Inhalt: |
xv
309 S. 27 s/w Illustr. 64 farbige Illustr. 309 p. 91 illus. 64 illus. in color. |
| ISBN-13: | 9789819929504 |
| ISBN-10: | 9819929504 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: |
Tsukada, Makoto
Kobayashi, Yuji Noguchi, Masato Takahasi, Sin-Ei Shirayanagi, Kiyoshi Kaneko, Hiroshi |
| Auflage: | 1st ed. 2023 |
| Hersteller: |
Springer Singapore
Springer Nature Singapore Springer Undergraduate Texts in Mathematics and Technology |
| Maße: | 260 x 183 x 24 mm |
| Von/Mit: | Makoto Tsukada (u. a.) |
| Erscheinungsdatum: | 07.12.2023 |
| Gewicht: | 0,809 kg |
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.
Gives a unified overview of various phenomena with linear structure from the perspective of functional analysis
Makes it enjoyable to learn linear algebra with Python by performing linear calculations without manual calculations
Handles large data such as images and sound using Python and deepens the understanding of linear structures
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Arithmetik & Algebra |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Seiten: | 324 |
| Reihe: | Springer Undergraduate Texts in Mathematics and Technology |
| Inhalt: |
xv
309 S. 27 s/w Illustr. 64 farbige Illustr. 309 p. 91 illus. 64 illus. in color. |
| ISBN-13: | 9789819929504 |
| ISBN-10: | 9819929504 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: |
Tsukada, Makoto
Kobayashi, Yuji Noguchi, Masato Takahasi, Sin-Ei Shirayanagi, Kiyoshi Kaneko, Hiroshi |
| Auflage: | 1st ed. 2023 |
| Hersteller: |
Springer Singapore
Springer Nature Singapore Springer Undergraduate Texts in Mathematics and Technology |
| Maße: | 260 x 183 x 24 mm |
| Von/Mit: | Makoto Tsukada (u. a.) |
| Erscheinungsdatum: | 07.12.2023 |
| Gewicht: | 0,809 kg |
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