Generating a normal distribution to a given distribution

Hi, I am having trouble with this question, can someone help me ASAP.

Generate N = 1000 samples from a standard normal distribution (zero mean, identity covariance) and transform these samples to be distributed as:

X= [x1,x2]T  ~  N(μ, Σ),    μ=[1,1]T,  Σ=    2   -1
                                            -1    1

This asks to plot on matlab. I am new to matlab

[John D'Errico]

If you choose to use arbitrary notation of your own choosing, expect people to have a hard time understanding what you are asking.

For example, what do you mean by this? Is the T supposed to indicate transpose?

[x1,x2]T

Why not simply state that you want to generate vectors of size 2 by 1, thus column vectors?

Anyway, is there a reason not to simply use mvnrnd?

[fafz1203]

yes John I mean transpose, It would not let me right it a superscript

[fafz1203]

Yes I want to generate column vectors of size 2*1, I just wanted to show the mean is 0 and the covariance is identity.