Page 83 - Basics of MATLAB and Beyond
P. 83

Beyond the Basics







                               Prelude

                               This part of the book assumes that you already have some competency
                               with matlab. You may have been using it for a while and you find you
                               want to do more with it. Perhaps you have seen what other people do
                               and are wondering how it is done. Well, read on.
                                  This part of the book follows an introductory course in matlab
                               (Part I) that covered the basics: matrices, typing shortcuts, basic graph-
                               ics, basic algebra and data analysis, basics of m-files and data files, and
                               a few simple applications, such as curve fitting, FFTs, and sound. Basic
                               handle graphics were introduced using set and get.
                                  We begin by looking at sparse matrices and strings, go on to deal
                               with some of the data types that are new to matlab version 5: cell
                               arrays, multidimensional arrays and structures, then deal with a variety
                               of topics that you will probably have to deal with at some stage if you are
                               a frequent user of matlab. The book can be worked through from start
                               to finish, but if you are not interested in a particular topic, you can skip
                               over it without affecting your understanding of later topics. Exercises
                               are given throughout the book, and answers to most of them are given
                               at the end. We start by introducing some new variable types that go
                               beyond the functionality of a rectangular matrix.


                               25    Sparse Arrays

                               In some applications, matrices have only a few non-zero elements. Such
                               matrices might arise, for example, when analysing communication net-
                               works or when performing finite element modelling. matlab provides
                               sparse arrays for dealing with such cases. Sparse arrays take up much
                               less storage space and calculation time than full arrays.



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