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Linear algebra for computational sci...
~
Neri, Ferrante.
Linear algebra for computational sciences and engineering
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Linear algebra for computational sciences and engineeringby Ferrante Neri.
作者:
Neri, Ferrante.
出版者:
Cham :Springer International Publishing :2019.
面頁冊數:
xxv, 574 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer eBooks
標題:
Algebras, Linear.
電子資源:
https://doi.org/10.1007/978-3-030-21321-3
ISBN:
9783030213213$q(electronic bk.)
Linear algebra for computational sciences and engineering
Neri, Ferrante.
Linear algebra for computational sciences and engineering
[electronic resource] /by Ferrante Neri. - 2nd ed. - Cham :Springer International Publishing :2019. - xxv, 574 p. :ill. (some col.), digital ;24 cm.
1. Basic Mathematical Thinking -- 2. Matrices -- 3. Systems of Linear Equations -- 4. Geometric Vectors -- 5. Complex Numbers and Polynomials -- 6. An Introduction to Geometric Algebra and Conics -- 7. An Overview of Algebraic Structures -- 8. Vector Spaces -- 9. An Introduction to Inner Product Spaces: Euclidean Spaces -- 10. Linear Mappings -- 11. An Introduction to Computational Complexity -- 12. Graph Theory -- 13. Applied Linear Algebra: Electrical Networks -- A. non-linear Algebra: An Introduction to Boolean Algebra -- Proofs of Theorems that Require Further Knowledge of Mathematics -- Appendix. Solutions to the Exercises.
This book presents the main concepts of linear algebra from the viewpoint of applied scientists such as computer scientists and engineers, without compromising on mathematical rigor. Based on the idea that computational scientists and engineers need, in both research and professional life, an understanding of theoretical concepts of mathematics in order to be able to propose research advances and innovative solutions, every concept is thoroughly introduced and is accompanied by its informal interpretation. Furthermore, most of the theorems included are first rigorously proved and then shown in practice by a numerical example. When appropriate, topics are presented also by means of pseudocodes, thus highlighting the computer implementation of algebraic theory. It is structured to be accessible to everybody, from students of pure mathematics who are approaching algebra for the first time to researchers and graduate students in applied sciences who need a theoretical manual of algebra to successfully perform their research. Most importantly, this book is designed to be ideal for both theoretical and practical minds and to offer to both alternative and complementary perspectives to study and understand linear algebra.
ISBN: 9783030213213$q(electronic bk.)
Standard No.: 10.1007/978-3-030-21321-3doiSubjects--Topical Terms:
183087
Algebras, Linear.
LC Class. No.: QA184.2 / .N47 2019
Dewey Class. No.: 512.5
Linear algebra for computational sciences and engineering
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1. Basic Mathematical Thinking -- 2. Matrices -- 3. Systems of Linear Equations -- 4. Geometric Vectors -- 5. Complex Numbers and Polynomials -- 6. An Introduction to Geometric Algebra and Conics -- 7. An Overview of Algebraic Structures -- 8. Vector Spaces -- 9. An Introduction to Inner Product Spaces: Euclidean Spaces -- 10. Linear Mappings -- 11. An Introduction to Computational Complexity -- 12. Graph Theory -- 13. Applied Linear Algebra: Electrical Networks -- A. non-linear Algebra: An Introduction to Boolean Algebra -- Proofs of Theorems that Require Further Knowledge of Mathematics -- Appendix. Solutions to the Exercises.
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This book presents the main concepts of linear algebra from the viewpoint of applied scientists such as computer scientists and engineers, without compromising on mathematical rigor. Based on the idea that computational scientists and engineers need, in both research and professional life, an understanding of theoretical concepts of mathematics in order to be able to propose research advances and innovative solutions, every concept is thoroughly introduced and is accompanied by its informal interpretation. Furthermore, most of the theorems included are first rigorously proved and then shown in practice by a numerical example. When appropriate, topics are presented also by means of pseudocodes, thus highlighting the computer implementation of algebraic theory. It is structured to be accessible to everybody, from students of pure mathematics who are approaching algebra for the first time to researchers and graduate students in applied sciences who need a theoretical manual of algebra to successfully perform their research. Most importantly, this book is designed to be ideal for both theoretical and practical minds and to offer to both alternative and complementary perspectives to study and understand linear algebra.
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