To identify which lines of code consume the most time or which lines MATLAB does not run, profile your code.
When you run the Profiler on a file, some code might
not run, such as a block containing an
To determine how much of a file MATLAB executed when you profiled
it, run the Coverage Report.
To speed up the performance of your code, there are several techniques that you can consider.
that incrementally increases the size of an array each time through
the loop can adversely affect performance and memory use. Often you
can improve code execution time by preallocating the maximum amount
of space required for the array.
You can revise loop-based, scalar-oriented code to use MATLAB matrix and vector operations. Vectorizing your code can make it easier to understand, less error prone, and faster to execute.