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Prove the Theorem 3(d) i.e., \({\left( {AB} \right)^T} = {B^T}{A^T}\).

Short Answer

Expert verified

The ijth entry of \({\left( {AB} \right)^T}\) and \({B^T}{A^T}\) is equal. Hence, \({\left( {AB} \right)^T} = {B^T}{A^T}\).

Step by step solution

01

Write the ijth entry of \({\left( {AB} \right)^T}\)

Let A and B be the matrices of sizes \(m \times n\) and \(n \times k\), respectively.

Note that the ijth entry of \({\left( {AB} \right)^T}\) is the jith entry of \(AB\). That is,

\({a_{j1}}{b_{1i}} + {a_{j2}}{b_{2i}} + ... + {a_{jn}}{b_{ni}}\).

02

Write the ijth entry of \({B^T}{A^T}\)

The ith row of \({B^T}\) is \(\left( {\begin{aligned}{*{20}{c}}{{b_{1i}}}&{{b_{2i}}}&{...}&{{b_{ni}}}\end{aligned}} \right)\), and the jth column of \({A^T}\) is \(\left( {\begin{aligned}{*{20}{c}}{{a_{j1}}}\\{{a_{j2}}}\\ \vdots \\{{a_{jn}}}\end{aligned}} \right)\). Then ijth entry of \({B^T}{A^T}\) is \({b_{1i}}{a_{j1}} + {b_{2i}}{a_{j2}} + ... + {b_{ni}}{a_{jn}} = {a_{j1}}{b_{1i}} + {a_{j2}}{b_{2i}} + ... + {a_{jn}}{b_{ni}}\).

03

Draw a conclusion

Hence, the ijth entry of \({\left( {AB} \right)^T}\) and \({B^T}{A^T}\) is equal. This implies, \({\left( {AB} \right)^T} = {B^T}{A^T}\).

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Most popular questions from this chapter

Prove Theorem 2(b) and 2(c). Use the row-column rule. The \(\left( {i,j} \right)\)- entry in \(A\left( {B + C} \right)\) can be written as \({a_{i1}}\left( {{b_{1j}} + {c_{1j}}} \right) + ... + {a_{in}}\left( {{b_{nj}} + {c_{nj}}} \right)\) or \(\sum\limits_{k = 1}^n {{a_{ik}}\left( {{b_{kj}} + {c_{kj}}} \right)} \).

Show that block upper triangular matrix \(A\) in Example 5is invertible if and only if both \({A_{{\bf{11}}}}\) and \({A_{{\bf{12}}}}\) are invertible. [Hint: If \({A_{{\bf{11}}}}\) and \({A_{{\bf{12}}}}\) are invertible, the formula for \({A^{ - {\bf{1}}}}\) given in Example 5 actually works as the inverse of \(A\).] This fact about \(A\) is an important part of several computer algorithims that estimates eigenvalues of matrices. Eigenvalues are discussed in chapter 5.

Let \(T:{\mathbb{R}^n} \to {\mathbb{R}^n}\) be an invertible linear transformation. Explain why T is both one-to-one and onto \({\mathbb{R}^n}\). Use equations (1) and (2). Then give a second explanation using one or more theorems.

Suppose \({A_{{\bf{11}}}}\) is an invertible matrix. Find matrices Xand Ysuch that the product below has the form indicated. Also,compute \({B_{{\bf{22}}}}\). [Hint:Compute the product on the left, and setit equal to the right side.]

\[\left[ {\begin{array}{*{20}{c}}I&{\bf{0}}&{\bf{0}}\\X&I&{\bf{0}}\\Y&{\bf{0}}&I\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{A_{{\bf{1}}1}}}&{{A_{{\bf{1}}2}}}\\{{A_{{\bf{2}}1}}}&{{A_{{\bf{2}}2}}}\\{{A_{{\bf{3}}1}}}&{{A_{{\bf{3}}2}}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\{\bf{0}}&{{B_{22}}}\\{\bf{0}}&{{B_{32}}}\end{array}} \right]\]

Prove Theorem 2(d). (Hint: The \(\left( {i,j} \right)\)- entry in \(\left( {rA} \right)B\) is \(\left( {r{a_{i1}}} \right){b_{1j}} + ... + \left( {r{a_{in}}} \right){b_{nj}}\).)

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