Numerical Analysis Using Sage

  • George A. Anastassiou
  • Razvan A. Mezei

Table of contents

  1. Front Matter
    Pages i-xii
  2. George A. Anastassiou, Razvan A. Mezei
    Pages 1-63
  3. George A. Anastassiou, Razvan A. Mezei
    Pages 65-115
  4. George A. Anastassiou, Razvan A. Mezei
    Pages 117-159
  5. George A. Anastassiou, Razvan A. Mezei
    Pages 161-173
  6. George A. Anastassiou, Razvan A. Mezei
    Pages 175-225
  7. George A. Anastassiou, Razvan A. Mezei
    Pages 227-261
  8. George A. Anastassiou, Razvan A. Mezei
    Pages 263-311
  9. George A. Anastassiou, Razvan A. Mezei
    Pages E1-E1
  10. Back Matter
    Pages 313-314

About this book

Introduction

This is the first numerical analysis text to use Sage for the implementation of algorithms and can be used in a one-semester course for undergraduates in mathematics, math education, computer science/information technology, engineering, and physical sciences. The primary aim of this text is to simplify understanding of the theories and ideas from a numerical analysis/numerical methods course via a modern programming language like Sage. Aside from the presentation of fundamental theoretical notions of numerical analysis throughout the text, each chapter concludes with several exercises that are oriented to real-world application.  Answers may be verified using Sage. 

The presented code, written in core components of Sage, are backward compatible, i.e., easily applicable to other software systems such as Mathematica®.  Sage is  open source software and uses Python-like syntax. Previous Python programming experience is not a requirement for the reader, though familiarity with any programming language is a plus.  Moreover, the code can be written using any web browser and is therefore useful with Laptops, Tablets, iPhones, Smartphones, etc.  All Sage code that is presented in the text is openly available on SpringerLink.com.

Keywords

Sage Math algorithms Sage numerical analysis Sage python algorithms python syntax textbook adoption

Authors and affiliations

  • George A. Anastassiou
    • 1
  • Razvan A. Mezei
    • 2
  1. 1.Department of Mathematical SciencesThe University of MemphisMemphisUSA
  2. 2.Mathematics & Computing SciencesLenoir-Rhyne UniversityHickoryUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-16739-8
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-16738-1
  • Online ISBN 978-3-319-16739-8
  • Series Print ISSN 1867-5506
  • Series Online ISSN 1867-5514
  • About this book