Find an SVD of the indicated matrix.

$$A = \left[ \begin{array} { r r } { 0 } & { - 2 } \\ { - 3 } & { 0 } \end{array} \right]$$

Find an SVD of the indicated matrix.

$$A = \left[ \begin{array} { r r } { 1 } & { - 1 } \\ { 1 } & { 1 } \end{array} \right]$$

Find an SVD of each matrix in the below Exercise.

$$\left[\begin{array}{rr}-2 & 0 \\ 0 & 0\end{array}\right]$$

Find an SVD of each matrix.

$$\left[ \begin{array}{rr}{-2} & {0} \\ {0} & {0}\end{array}\right]$$

Find an SVD of matrix.

$$\left[\begin{array}{ll} 2 & 3 \\ 0 & 2 \end{array}\right]$$

Find an SVD of each matrix.

$$\left[ \begin{array}{rr}{3} & {-3} \\ {0} & {0} \\ {1} & {1}\end{array}\right]$$

A single-replacement reaction occurs between copper and silver nitrate. When 63.5 g of copper reacts with 339.8 g of silver nitrate, 215.S g of silver is produced. Write a balanced chemical equation for this reaction. What other product formed? What is the mass of the second product?

Find an SVD of matrix.

$$\left[\begin{array}{ll} 7 & 1 \\ 0 & 0 \\ 5 & 5 \end{array}\right]$$

Find an SVD of the indicated matrix.

$$A = \left[ \begin{array} { l l } { 1 } & { 1 } \\ { 1 } & { 1 } \end{array} \right]$$

Assume that A is an $n \times n$ matrix with SVD $A=U \Sigma V^{T}$. If A is invertible, find a SVD of $A^{-1}$.

Find an SVD of each matrix in the below Exercise.

$$\left[\begin{array}{rr}-3 & 0 \\ 0 & -2\end{array}\right]$$

Find the SVD of the following matrices by hand calculation: (a)

$$\left[ \begin{array} { l l } { 3 } & { 0 } \\ { 4 } & { 0 } \end{array} \right]$$

, (b)

$$\left[ \begin{array} { r r } { 6 } & { - 2 } \\ { 8 } & { \frac { 3 } { 2 } } \end{array} \right]$$

, (c)

$$\left[ \begin{array} { l l } { 0 } & { 1 } \\ { 0 } & { 0 } \end{array} \right]$$

, (d)

$$\left[ \begin{array} { r r } { - 4 } & { - 12 } \\ { 12 } & { 11 } \end{array} \right]$$

, (e)

$$\left[ \begin{array} { r r } { 0 } & { - 2 } \\ { - 1 } & { 0 } \end{array} \right]$$

Simplify: 1 kg - 75 g

Find the SVD of

$$A=\left[\begin{array}{rrr}3 & 2 & 2 \\ 2 & 3 & -2\end{array}\right]$$

[Hint: Work with $A^T$.]