Using matrices is a difficult concept to grasp at first but it's an extremely useful tool once you understand, for that reason I am going to try and explain it here.
I have set up your equations in the form
[tex]Ax = b[/tex]
Where A is your matrix of known values, x is your column vector of unknowns, which is what you're trying to solve for, and b is also a column vector you know.
To expand out a system like this you have to multiply each ROW of A by the column vector x and set it equal to the corresponding ROW in b (which is just a single value, in this case we have 4 0's and one E_1)
For example, for the first row we have
[tex]\left[ {\begin{array}{cc}<br />
1 & 1 & -1 & 0 & 0<br />
\end{array} } \right]<br />
\left[ {\begin{array}{cc}<br />
I_{1}\\<br />
I_{2}\\<br />
I_{3}\\<br />
I_{4}\\<br />
I_{5}\\<br />
\end{array} } \right]<br />
=<br />
0[/tex]
We multiply across the row and down the column.
[tex]1*I_{1} + 1*I_{2} - 1*I_{3} + 0*I_{4} + 0*I_{5} = 0[/tex]
Simplifying this we get back the original first equation:
[tex]I_{1} + I_{2} = I_{3}[/tex]
As an exercise try doing this with each row and you'll see that you get back your original equations. To be more explicit I am going to do the same thing with the last row so you see a more complicated example: ***I made a mistake in my previous post in the last row, the [itex]R_{4}[/itex] should be an [itex]R_{5}[/itex] *****
[tex]\left[ {\begin{array}{cc}<br />
0 & R_{2} & R_{3} & 0 & R_{5}<br />
\end{array} } \right]<br />
\left[ {\begin{array}{cc}<br />
I_{1}\\<br />
I_{2}\\<br />
I_{3}\\<br />
I_{4}\\<br />
I_{5}\\<br />
\end{array} } \right]<br />
=<br />
E_{1}[/tex]
Expanding out we get:
[tex]0*I_{1} + R_{2}*I_{2} + R_{3}*I_{3} + 0*I_{4} + R_{5}*I_{5} = E_{1}[/tex]
Simplifying we can get back the original 5th equation:
[tex]E_{1} - R_{2}I_{2} - R_{3}I_{3} - R_{5}I_{5} = 0[/tex]
Now the way to solve this system is to row-reduce the matrix. Rather.. put it in the following form:
[tex]
\left[ {\begin{array}{cc}<br />
1 & 1 & -1 & 0 & 0 \\<br />
0 & 1 & X & X & X \\<br />
0 & 0 & 1 & X & X \\<br />
0 & 0 & 0 & 1 & X \\<br />
0 & 0 & 0 & 0 & 1 \\<br />
\end{array} } \right]<br />
\left[ {\begin{array}{cc}<br />
I_{1}\\<br />
I_{2}\\<br />
I_{3}\\<br />
I_{4}\\<br />
I_{5}\\<br />
\end{array} } \right]<br />
=<br />
\left[ {\begin{array}{cc}<br />
0\\<br />
0\\<br />
0\\<br />
0\\<br />
X\\<br />
\end{array} } \right][/tex]
The X's are there because the process of row-reducing MAY change what these values are.
By doing this process we end up being able to re-expand everything and get a something equivalent to our original equations but incredibly simple to solve for the currents. As you may see if we were to expand out the last row we would get [itex]I_{5} = X[/itex] The X will depend on the process of row reducing and simplifying.
I think it would be easier at this point to substitute in numbers in our matrix. The values I can read from your pictures produce the following (correct me if I'm wrong):
[tex]
\left[ {\begin{array}{cc}<br />
1 & 1 & -1 & 0 & 0 \\<br />
0 & 0 & -1 & 1 & 1 \\<br />
-10.6 & 5.00 & 0 & 0 & 0 \\<br />
0 & 0 & 0 & -10.2 & 5.00 \\<br />
0 & 5.00 & 34.5 & 0 & 5.00 \\<br />
\end{array} } \right]<br />
\left[ {\begin{array}{cc}<br />
I_{1}\\<br />
I_{2}\\<br />
I_{3}\\<br />
I_{4}\\<br />
I_{5}\\<br />
\end{array} } \right]<br />
=<br />
\left[ {\begin{array}{cc}<br />
0\\<br />
0\\<br />
0\\<br />
0\\<br />
9.9\\<br />
\end{array} } \right][/tex]
You said you have worked with matrices in the past so I am going to stop here. Hopefully it has refreshed your memory on how to row-reduce. If not then I can continue on and give you a little more guidance as to how to procede