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.
