If \(A = \left( {\begin{aligned}{*{20}{c}}1&{ - 2}\\{ - 2}&5\end{aligned}} \right)\) and \(AB = \left( {\begin{aligned}{*{20}{c}}{ - 1}&2&{ - 1}\\6&{ - 9}&3\end{aligned}} \right)\), determine the first and second column of B.

Short Answer

Expert verified

The first and second columns of matrix \(B\) are \(\left( {\begin{aligned}{*{20}{c}}7\\4\end{aligned}} \right)\) and \(\left( {\begin{aligned}{*{20}{c}}{ - 8}\\{ - 5}\end{aligned}} \right)\), respectively.

Step by step solution

01

Definition of matrix multiplication

Consider two matrices P and Q of order\(m \times n\)and\(n \times p\), respectively. The order of the product PQ matrix is\(m \times p\).

Let\({{\bf{q}}_1},{{\bf{q}}_2},...,{{\bf{q}}_n}\)be the columns of the matrix Q. Then, the product PQ is obtained as shown below:

\(\begin{aligned}{c}PQ = P\left( {\begin{aligned}{*{20}{c}}{{{\bf{q}}_1}}&{{{\bf{q}}_2}}& \cdots &{{{\bf{q}}_n}}\end{aligned}} \right)\\ = \left( {\begin{aligned}{*{20}{c}}{P{{\bf{q}}_1}}&{P{{\bf{q}}_2}}& \cdots &{P{{\bf{q}}_n}}\end{aligned}} \right)\end{aligned}\)

02

Construct the general matrix B

Let\({{\bf{b}}_1},{{\bf{b}}_2},{{\bf{b}}_3}\)be the columns of matrix B. Then, the product AB is obtained as shown below:

\(\begin{aligned}{c}AB = A\left( {\begin{aligned}{*{20}{c}}{{{\bf{b}}_1}}&{{{\bf{b}}_2}}&{{{\bf{b}}_3}}\end{aligned}} \right)\\ = \left( {A\begin{aligned}{*{20}{c}}{{{\bf{b}}_1}}&{A{{\bf{b}}_2}}&{A{{\bf{b}}_3}}\end{aligned}} \right)\end{aligned}\)

And the given product AB is\(AB = \left( {\begin{aligned}{*{20}{c}}{ - 1}&2&{ - 1}\\6&{ - 9}&3\end{aligned}} \right)\).

Compare \(AB = \left( {A\begin{aligned}{*{20}{c}}{{{\bf{b}}_1}}&{A{{\bf{b}}_2}}&{A{{\bf{b}}_3}}\end{aligned}} \right)\) and \(AB = \left( {\begin{aligned}{*{20}{c}}{ - 1}&2&{ - 1}\\6&{ - 9}&3\end{aligned}} \right)\). So, \(A{{\bf{b}}_1} = \left( {\begin{aligned}{*{20}{c}}{ - 1}\\6\end{aligned}} \right)\), and \(A{{\bf{b}}_2} = \left( {\begin{aligned}{*{20}{c}}2\\{ - 9}\end{aligned}} \right)\).

03

Obtain the first column of matrix B

Let,\({{\bf{b}}_1} = \left( {\begin{aligned}{*{20}{c}}{{x_1}}\\{{x_2}}\end{aligned}} \right)\). Then, it can be written as shown below:

\(\begin{aligned}{c}A{{\bf{b}}_1} = \left( {\begin{aligned}{*{20}{c}}{ - 1}\\6\end{aligned}} \right)\\\left( {\begin{aligned}{*{20}{c}}1&{ - 2}\\{ - 2}&5\end{aligned}} \right)\left( {\begin{aligned}{*{20}{c}}{{x_1}}\\{{x_2}}\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}{ - 1}\\6\end{aligned}} \right)\end{aligned}\)

In augmented form,

\(\left( {\begin{aligned}{*{20}{c}}1&{ - 2}&{ - 1}\\{ - 2}&5&6\end{aligned}} \right)\)

Use\({x_1}\)term in the first equation to eliminate\( - 2{x_1}\)term from the second equation. Add 2 times row 1 to row 2.

\(\left( {\begin{aligned}{*{20}{c}}1&{ - 2}&{ - 1}\\{ - 2}&5&6\end{aligned}} \right) \sim \left( {\begin{aligned}{*{20}{c}}1&{ - 2}&{ - 1}\\0&1&4\end{aligned}} \right)\)

Use\({x_2}\)term in the second equation to eliminate\( - 2{x_2}\)term from the first equation. Add 2 times row 2 to row 1.

\(\left( {\begin{aligned}{*{20}{c}}1&{ - 2}&{ - 1}\\0&1&4\end{aligned}} \right) \sim \left( {\begin{aligned}{*{20}{c}}1&0&7\\0&1&4\end{aligned}} \right)\)

Thus, the row reduced echelon form is\(\left( {\begin{aligned}{*{20}{c}}1&0&7\\0&1&4\end{aligned}} \right)\).

So, \({x_1} = 7\), and \({x_2} = 4\).

Therefore, the first column of matrix B is \(\left( {\begin{aligned}{*{20}{c}}7\\4\end{aligned}} \right)\).

04

Obtain the second column of matrix B

Let,\({{\bf{b}}_2} = \left( {\begin{aligned}{*{20}{c}}{{x_1}}\\{{x_2}}\end{aligned}} \right)\). Then, it can be written as shown below:

\(\begin{aligned}{c}A{{\bf{b}}_2} = \left( {\begin{aligned}{*{20}{c}}2\\{ - 9}\end{aligned}} \right)\\\left( {\begin{aligned}{*{20}{c}}1&{ - 2}\\{ - 2}&5\end{aligned}} \right)\left( {\begin{aligned}{*{20}{c}}{{x_1}}\\{{x_2}}\end{aligned}} \right) = \left( {\begin{aligned}{*{20}{c}}2\\{ - 9}\end{aligned}} \right)\end{aligned}\)

In augmented form,

\(\left( {\begin{aligned}{*{20}{c}}1&{ - 2}&2\\{ - 2}&5&{ - 9}\end{aligned}} \right)\)

Use\({x_1}\)term in the first equation to eliminate\( - 2{x_1}\)term from the second equation. Add 2 times row 1 to row 2.

\(\left( {\begin{aligned}{*{20}{c}}1&{ - 2}&2\\{ - 2}&5&{ - 9}\end{aligned}} \right) \sim \left( {\begin{aligned}{*{20}{c}}1&{ - 2}&2\\0&1&{ - 5}\end{aligned}} \right)\)

Use\({x_2}\)term in the second equation to eliminate\( - 2{x_2}\)term from the first equation. Add 2 times row 2 to row 1.

\(\left( {\begin{aligned}{*{20}{c}}1&{ - 2}&2\\0&1&{ - 5}\end{aligned}} \right) \sim \left( {\begin{aligned}{*{20}{c}}1&0&{ - 8}\\0&1&{ - 5}\end{aligned}} \right)\)

Thus, the row reduced echelon form is\(\left( {\begin{aligned}{*{20}{c}}1&0&{ - 8}\\0&1&{ - 5}\end{aligned}} \right)\).

So, \({x_1} = - 8\), and \({x_2} = - 5\).

Therefore, the first column of matrix B is \(\left( {\begin{aligned}{*{20}{c}}{ - 8}\\{ - 5}\end{aligned}} \right)\).

Thus, the first and second columns of matrix B are \(\left( {\begin{aligned}{*{20}{c}}7\\4\end{aligned}} \right)\) and \(\left( {\begin{aligned}{*{20}{c}}{ - 8}\\{ - 5}\end{aligned}} \right)\), respectively.

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Most popular questions from this chapter

Suppose Ais \(n \times n\) and the equation \(A{\bf{x}} = {\bf{0}}\) has only the trivial solution. Explain why Ahas npivot columns and Ais row equivalent to \({I_n}\). By Theorem 7, this shows that Amust be invertible. (This exercise and Exercise 24 will be cited in Section 2.3.)

In Exercises 1 and 2, compute each matrix sum or product if it is defined. If an expression is undefined, explain why. Let

\(A = \left( {\begin{aligned}{*{20}{c}}2&0&{ - 1}\\4&{ - 5}&2\end{aligned}} \right)\), \(B = \left( {\begin{aligned}{*{20}{c}}7&{ - 5}&1\\1&{ - 4}&{ - 3}\end{aligned}} \right)\), \(C = \left( {\begin{aligned}{*{20}{c}}1&2\\{ - 2}&1\end{aligned}} \right)\), \(D = \left( {\begin{aligned}{*{20}{c}}3&5\\{ - 1}&4\end{aligned}} \right)\) and \(E = \left( {\begin{aligned}{*{20}{c}}{ - 5}\\3\end{aligned}} \right)\)

\( - 2A\), \(B - 2A\), \(AC\), \(CD\).

A useful way to test new ideas in matrix algebra, or to make conjectures, is to make calculations with matrices selected at random. Checking a property for a few matrices does not prove that the property holds in general, but it makes the property more believable. Also, if the property is actually false, you may discover this when you make a few calculations.

38. Use at least three pairs of random \(4 \times 4\) matrices Aand Bto test the equalities \({\left( {A + B} \right)^T} = {A^T} + {B^T}\) and \({\left( {AB} \right)^T} = {A^T}{B^T}\). (See Exercise 37.) Report your conclusions. (Note:Most matrix programs use \(A'\) for \({A^{\bf{T}}}\).

(M) Read the documentation for your matrix program, and write the commands that will produce the following matrices (without keying in each entry of the matrix).

  1. A \({\bf{5}} \times {\bf{6}}\) matrix of zeros
  2. A \({\bf{3}} \times {\bf{5}}\) matrix of ones
  3. The \({\bf{6}} \times {\bf{6}}\) identity matrix
  4. A \({\bf{5}} \times {\bf{5}}\) diagonal matrix, with diagonal entries 3, 5, 7, 2, 4

Let \(X\) be \(m \times n\) data matrix such that \({X^T}X\) is invertible., and let \(M = {I_m} - X{\left( {{X^T}X} \right)^{ - {\bf{1}}}}{X^T}\). Add a column \({x_{\bf{0}}}\) to the data and form

\(W = \left[ {\begin{array}{*{20}{c}}X&{{x_{\bf{0}}}}\end{array}} \right]\)

Compute \({W^T}W\). The \(\left( {{\bf{1}},{\bf{1}}} \right)\) entry is \({X^T}X\). Show that the Schur complement (Exercise 15) of \({X^T}X\) can be written in the form \({\bf{x}}_{\bf{0}}^TM{{\bf{x}}_{\bf{0}}}\). It can be shown that the quantity \({\left( {{\bf{x}}_{\bf{0}}^TM{{\bf{x}}_{\bf{0}}}} \right)^{ - {\bf{1}}}}\) is the \(\left( {{\bf{2}},{\bf{2}}} \right)\)-entry in \({\left( {{W^T}W} \right)^{ - {\bf{1}}}}\). This entry has a useful statistical interpretation, under appropriate hypotheses.

In the study of engineering control of physical systems, a standard set of differential equations is transformed by Laplace transforms into the following system of linear equations:

\(\left[ {\begin{array}{*{20}{c}}{A - s{I_n}}&B\\C&{{I_m}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{\bf{x}}\\{\bf{u}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{\bf{0}}\\{\bf{y}}\end{array}} \right]\)

Where \(A\) is \(n \times n\), \(B\) is \(n \times m\), \(C\) is \(m \times n\), and \(s\) is a variable. The vector \({\bf{u}}\) in \({\mathbb{R}^m}\) is the “input” to the system, \({\bf{y}}\) in \({\mathbb{R}^m}\) is the “output” and \({\bf{x}}\) in \({\mathbb{R}^n}\) is the “state” vector. (Actually, the vectors \({\bf{x}}\), \({\bf{u}}\) and \({\bf{v}}\) are functions of \(s\), but we suppress this fact because it does not affect the algebraic calculations in Exercises 19 and 20.)

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