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Analysis for Computer Scientists: Foundations, Methods, and Algorithms

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Mathematics and mathematical modelling are of central importance in computer science, and therefore it is vital that computer scientists are aware of the latest concepts and techniques. This concise and easy-to-read textbook/reference presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating m Mathematics and mathematical modelling are of central importance in computer science, and therefore it is vital that computer scientists are aware of the latest concepts and techniques. This concise and easy-to-read textbook/reference presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating mathematical software into the text as an important component of analysis, the book makes thorough use of examples and explanations using MATLAB, Maple, and Java applets. Mathematical theory is described alongside the basic concepts and methods of numerical analysis, supported by computer experiments and programming exercises, and an extensive use of figure illustrations. Topics and features: thoroughly describes the essential concepts of analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives and antiderivatives, definite integrals and double integrals, and curves; provides summaries and exercises in each chapter, as well as computer experiments; discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes definitions, propositions and examples throughout the text, together with a list of relevant textbooks and references for further reading; supplementary software can be downloaded from the book's webpage at www.springer.com. This textbook is essential for undergraduate students in Computer Science. Written to specifically address the needs of computer scientists and researchers, it will also serve professionals looking to bolster their knowledge in such fundamentals extremely well.


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Mathematics and mathematical modelling are of central importance in computer science, and therefore it is vital that computer scientists are aware of the latest concepts and techniques. This concise and easy-to-read textbook/reference presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating m Mathematics and mathematical modelling are of central importance in computer science, and therefore it is vital that computer scientists are aware of the latest concepts and techniques. This concise and easy-to-read textbook/reference presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating mathematical software into the text as an important component of analysis, the book makes thorough use of examples and explanations using MATLAB, Maple, and Java applets. Mathematical theory is described alongside the basic concepts and methods of numerical analysis, supported by computer experiments and programming exercises, and an extensive use of figure illustrations. Topics and features: thoroughly describes the essential concepts of analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives and antiderivatives, definite integrals and double integrals, and curves; provides summaries and exercises in each chapter, as well as computer experiments; discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes definitions, propositions and examples throughout the text, together with a list of relevant textbooks and references for further reading; supplementary software can be downloaded from the book's webpage at www.springer.com. This textbook is essential for undergraduate students in Computer Science. Written to specifically address the needs of computer scientists and researchers, it will also serve professionals looking to bolster their knowledge in such fundamentals extremely well.

28 review for Analysis for Computer Scientists: Foundations, Methods, and Algorithms

  1. 4 out of 5

    Renee

    I can't even rate this book, it was too far over my head. But it seemed pretty serious. I can't even rate this book, it was too far over my head. But it seemed pretty serious.

  2. 4 out of 5

    John

  3. 4 out of 5

    Azmi_fa

  4. 4 out of 5

    H. Kemal Ilter

  5. 5 out of 5

    Gill

  6. 5 out of 5

    Kaiser

  7. 5 out of 5

    Greg

  8. 4 out of 5

    Noella Lum

  9. 4 out of 5

    Arun

  10. 4 out of 5

    Juk

  11. 5 out of 5

    Tim

  12. 4 out of 5

    Wendelle

  13. 4 out of 5

    Ryan

  14. 5 out of 5

    Mehrdad

  15. 4 out of 5

    Mohammed Ghabboun

  16. 4 out of 5

    Chesco Igual

  17. 5 out of 5

    E

  18. 4 out of 5

    Haksell

  19. 5 out of 5

    xsja

  20. 5 out of 5

    Kenneth Guffie

  21. 4 out of 5

    Matías

  22. 5 out of 5

    JMourad

  23. 4 out of 5

    Carol

  24. 5 out of 5

    Arttu Malek

  25. 5 out of 5

    A

  26. 5 out of 5

    Elton

  27. 5 out of 5

    Francesco Gerecitano

  28. 5 out of 5

    Bruce

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