Synopsis
Here is a short, well-written book that covers the material essential for learning LaTeX. It includes incisive examples that teach LaTeX in a powerful yet abbreviated fashion. This is the handbook to have if you don t want to wade through extraneous material. It includes the following crucial features: numerous examples of widely used mathematical expressions; complete documents illustrating the creation of articles, reports, presentations, and posters; troubleshooting tips to help you pinpoint an error; details of how to set up an index and a bibliography; and information about online LaTeX resources. Why do you need to learn LaTeX? LaTeX has become an extremely popular typesetting system and is widely used throughout the sciences. As a student, you may need to typeset reports and theses in LaTeX (particularly if you are a graduate student in any mathematics or computer science discipline). Or you may be someone who had planned to eventually get around to learning LaTeX, but you are still using older or less appropriate methods of typesetting. Procrastinate no more! This second edition of the well-regarded and highly successful book includes additional material on the American Mathematical Society packages for typesetting additional mathematical symbols and multi-line displays; the BiBTeX program for creating bibliographies; the Beamer package for creating presentations; and the a0poster class for creating posters.
À propos de l?auteur
David F. Griffiths, now retired, originally trained as an applied mathematician and, after a brief spell at New York University, spent his academic career at the University of Dundee, specialising in the numerical solution of differential equations. He has published three books and over fifty scientific articles on differential equations. Griffiths was joint organising secretary of the Dundee Biennial Conferences on Numerical Analysis from 1983 to 2005. Desmond J. Higham is a numerical analyst at the University of Strathclyde, Glasgow. His research interests are in stochastic computation, network science and city analytics. He is a SIAM Dahlquist Prize winner, a SIAM Fellow and a Fellow of the Royal Society of Edinburgh.
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