\( A = \left[ \begin{array} { c c c c c } { 25 } & { 16 } & { 0 } & { 0 } & { 1 } \\ { 0 } & { 8 } & { 12 } & { 0 } & { 0 } \\ { 0 } & { 0 } & { 1 } & { 0 } & { 0 } \\ { 8 } & { - 2 } & { 0 } & { 8 } & { 9 } \\ { 1 } & { 48 } & { 1 } & { 0 } & { 0 } \end{array} \right] , x = \left[ \begin{array} { l } { x _ { 1 } } \\ { x _ { 2 } } \\ { x _ { 3 } } \\ { x _ { 4 } } \\ { x _ { 5 } } \end{array} \right] , A x = \left[ \begin{array} { c } { 1 } \\ { 8 } \\ { 0 } \\ { 0 } \\ { 16 } \end{array} \right] \)
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Bonus Knowledge
Did you know that matrix equations like \(Ax = b\) are fundamental in various fields, including computer graphics, engineering, and economics? They allow us to represent complex systems and solve for unknown variables. In this particular array, each row can be thought of as a different equation, where the coefficients in front of \(x_i\) represent relationships among various quantities. If you're solving this matrix equation, always double-check if your matrix \(A\) is invertible. A common mistake is attempting to solve when \(A\) is singular (non-invertible), which can lead to no solutions or infinitely many solutions. To avoid this pitfall, calculate the determinant first, and if it's zero, you'll need alternative methods like row reduction or pseudoinverse to find \(x\). Happy solving!