Speeding-up builtin Matlab functions – part 1
Built-in Matlab functions can often be profiled and optimized for improved run-time performance. This article shows a typical example.
Built-in Matlab functions can often be profiled and optimized for improved run-time performance. This article shows a typical example.
The speed of the builtin csvwrite, dlmwrite functions can be improved dramatically.
Matlab's xmlread function cannot process XML data directly, but this can easily be overcome.
Parallelizing loops with Matlab's parfor might generate unexpected results. Users beware!
Password fields and spinner controls can easily be embedded in Matlab GUIs.
Fetching SQL ResultSet data from JDBC into Matlab can be made significantly faster.
A file-selector dialog window that includes an integrated preview panel is shown and explained.
The parfor (parallel for) loops can be made faster using a few simple tips.
Matlab's internal implementation of convolution can often be sped up significantly using the Convolution Theorem.
Java inner classes and enumerations can be used in Matlab with a bit of tweaking.