The most simple bootstrapping is just drawing samples repeatedly from your observations.
Say you have n observations. You draw k samples (k<=n, if k=n then it is full sample bootstrapping) each time. You would need to put the samples back to the observations after each drawing.
If your objective is mean value, then each draw gives you one mean. The entire bootstrapping (say 1000 draws) gives you 1000 means, which gives you a distribution of means. You can use the distribution for statistical inferences.
You can easily implement simple bootstrapping in Matlab using 'bootstrp' (or write a program yourself. it basically uses 'rand'). For higher level, you might need to write a program.