Julia syntax is mostly Matlab syntax with the parens-for-array-indexing replaced with square brackets. Its main shortcoming WRT Matlab is that it's a new language and a lot of things still need to be implemented, but the built-in linalg support is pretty good.
Python is also not that bad with pylab, which eliminates most of the verbosity of calling numpy/scipy functions directly, although it might still end up being more LOC than Matlab in some cases. I have only minimal experience with R, so I can't comment there.
So, I am back to Old Faithful. Really, I hate all languages, I just find Octave the least annoying in the mathematical programming space. (I used to love all languages, now I am old and bitter ;) )
Don't get me wrong -- lots of great ideas in all of the above languages. If Julia were to make vector / matrix thinking natural, I would switch.