Numerical Linear Algebra by Pavel Cížek, Lenka Cížková
Numerical Linear Algebra - Table of Contents
1. Matrix Decompositions
2. Direct Methods for Solving Linear Systems
3. Iterative Methods for Solving Linear Systems
4. Eigenvalues and Eigenvectors
5. Sparse Matrices
What You Will Learn in Numerical Linear Algebra
"Numerical Linear Algebra" by Pavel Cížek and Lenka Cížková is a focused academic book that explains how core ideas of "numerical methods", "matrix computations", and "linear systems" are used to solve real computational problems. The book connects classical linear algebra with practical algorithms needed for modern scientific and statistical work, helping readers understand not just theory, but how computations behave in practice.
The authors place strong emphasis on "algorithms", "stability", and "accuracy", showing how rounding errors and numerical limitations affect matrix operations. Topics such as solving large systems of equations, eigenvalue problems, and least-squares methods are discussed with attention to efficiency and reliability. This makes the book especially valuable for readers who want to see how linear algebra supports data analysis, optimization, and applied statistics.
Written in a clear and academic style, the book is best suited for advanced undergraduate and graduate students in mathematics, statistics, economics, and computational sciences. With its balance of theory and application, it serves as a solid resource for understanding how "numerical linear algebra" underpins many real-world algorithms and analytical tools used in research and industry.
Book Details & Specifications
Title:
Numerical Linear Algebra by Pavel Cížek, Lenka Cížková
Publisher:
Humboldt-Universität zu Berlin
Year:
2004
Pages:
37
Type:
PDF
Language:
English
ISBN-10 #:
N\A
ISBN-13 #:
N\A
License:
Creative Commons
Amazon:
Amazon
About the Author: Pavel Cížek, Lenka Cížková
The author
Pavel Cížek, Lenka Cížková
is a mathematician and academic whose work focuses on "numerical methods", "statistics", and "applied linear algebra". He has been associated with university-level teaching and research, where his interests include matrix computations, regression techniques, and quantitative analysis. His writing reflects a strong balance between mathematical theory and "computational practice", especially for students working with real data. "Lenka Cížková" is also an academic researcher with expertise in "numerical analysis", "linear algebra", and "statistical applications". She contributes to making complex mathematical ideas clearer through structured explanations and practical examples. Together, the authors combine "mathematical rigor" with applied insight, helping readers understand how linear algebra tools support modern numerical and statistical problem-solving.
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