/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q2.4-27Q [M] Suppose memory or size restr... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

[M] Suppose memory or size restrictions prevent your matrix program from working with matrices having more than 32 rows and 32 columns, and suppose some project involves \(50 \times 50\) matrices A and B. Describe the commands or operations of your program that accomplish the following tasks.

a. Compute \(A + B\)

b. Compute \(AB\)

c. Solve \(Ax = b\) for some vector b in \({\mathbb{R}^{50}}\), assuming that \(A\) can be partitioned into a \(2 \times 2\) block matrix \(\left[ {{A_{ij}}} \right]\), with \({A_{11}}\) an invertible \(20 \times 20\) matrix, \({A_{22}}\) an invertible \(30 \times 30\) matrix, and \({A_{12}}\) a zero matrix. [Hint: Describe appropriate smaller systems to solve, without using any matrix inverse.]

Short Answer

Expert verified

a. The MATLAB code to compute \(A + B\) is \[ > > {\mathop{\rm C}\nolimits} = \left[ {{\mathop{\rm C}\nolimits} 11\,\,{\mathop{\rm C}\nolimits} 12;\,\,{\mathop{\rm C}\nolimits} 21\,\,{\mathop{\rm C}\nolimits} 22} \right]\].

b. \(AB = \left[ {\begin{array}{*{20}{c}}{{A_{11}}{B_{11}} + {A_{12}}{B_{21}}}&{{A_{11}}{B_{12}} + {A_{12}}{B_{22}}}\\{{A_{21}}{B_{11}} + {A_{22}}{B_{21}}}&{{A_{21}}{B_{12}} + {A_{22}}{B_{22}}}\end{array}} \right]\)

c. The equation \({A_{11}}{{\mathop{\rm x}\nolimits} _1} = {{\mathop{\rm b}\nolimits} _1}\) and \({x_1}\) can be found by solving for \({{\mathop{\rm b}\nolimits} _1}\).

Step by step solution

01

Compute \(A + B\)

a)

Construct matrix A from four blocks as \({C_{11}},{C_{12}},{C_{21}},\) and \({C_{22}}\). Consider an example with \({C_{11}}\) as a \(30 \times 30\) matrix and \({C_{22}}\) as a \(20 \times 20\) matrix.

Use the MATLAB code to compute the matrix \(A + B\), as shown below:

\[\begin{array}{l} > > {\mathop{\rm C}\nolimits} 11 = {\mathop{\rm A}\nolimits} \left( {1:30,\,\,1:30} \right) + {\mathop{\rm B}\nolimits} \left( {1:30,\,\,1:30} \right)\\ > > {\mathop{\rm C}\nolimits} 11 = {\mathop{\rm A}\nolimits} \left( {1:30,\,\,1:30} \right) + {\mathop{\rm B}\nolimits} \left( {1:30,\,\,1:30} \right)\\ > > {\mathop{\rm C}\nolimits} 21 = {\mathop{\rm A}\nolimits} \left( {31:50,\,\,1:30} \right) + {\mathop{\rm B}\nolimits} \left( {31:50,\,\,1:30} \right)\\ > > {\mathop{\rm C}\nolimits} 22 = {\mathop{\rm A}\nolimits} \left( {31:50,\,\,31:50} \right) + {\mathop{\rm B}\nolimits} \left( {31:50,\,\,31:50} \right)\\ > > {\mathop{\rm C}\nolimits} = \left[ {{\mathop{\rm C}\nolimits} 11\,\,{\mathop{\rm C}\nolimits} 12;\,\,{\mathop{\rm C}\nolimits} 21\,\,{\mathop{\rm C}\nolimits} 22} \right]\end{array}\]

02

Compute \(AB\)

b)

The required algebra comes from block matrix multiplication, as shown below:

\[\begin{array}{c}AB = \left[ {\begin{array}{*{20}{c}}{{A_{11}}}&{{A_{12}}}\\{{A_{21}}}&{{A_{22}}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{B_{11}}}&{{B_{12}}}\\{{B_{21}}}&{{B_{22}}}\end{array}} \right]\\ = \left[ {\begin{array}{*{20}{c}}{{A_{11}}{B_{11}} + {A_{12}}{B_{21}}}&{{A_{11}}{B_{12}} + {A_{12}}{B_{22}}}\\{{A_{21}}{B_{11}} + {A_{22}}{B_{21}}}&{{A_{21}}{B_{12}} + {A_{22}}{B_{22}}}\end{array}} \right]\end{array}\]

Both matrices \(A\) and \(B\) can be partitioned, for example, in \(30 \times 30\)\(\left( {1,1} \right)\) blocks and \[20 \times 20\left( {2,2} \right)\] blocks. The four necessary submatrix calculations follow the same syntax as part (a).

03

Solve the equation \(Ax = b\) for vector b

c)

The required algebra comes from the block matrix equation shown below:

\(\left[ {\begin{array}{*{20}{c}}{{A_{11}}}&0\\{{A_{21}}}&{{A_{22}}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{x_1}}\\{{x_2}}\end{array}} \right] = \left[ {\begin{array}{*{20}{c}}{{b_1}}\\{{b_2}}\end{array}} \right]\)

Here, \({x_1}\) and \({{\mathop{\rm b}\nolimits} _1}\) are in \({\mathbb{R}^{30}}\)and \({x_2}\), \({{\mathop{\rm b}\nolimits} _2}\) are in \({\mathbb{R}^{20}}\). Hence, \({A_{11}}{{\mathop{\rm x}\nolimits} _1} = {{\mathop{\rm b}\nolimits} _1}\) and \({x_1}\) can be found by solving for \({{\mathop{\rm b}\nolimits} _1}\).

After determining \({x_1}\) , rewrite the equation \({A_{21}}{{\mathop{\rm x}\nolimits} _1} + {A_{22}}{{\mathop{\rm x}\nolimits} _2} = {{\mathop{\rm b}\nolimits} _2}\) as \({A_{22}}{{\mathop{\rm x}\nolimits} _2} = {\mathop{\rm c}\nolimits} \), where \({\mathop{\rm c}\nolimits} = {{\mathop{\rm b}\nolimits} _2} - {A_{21}}{x_1}\) , and solve the equation \({A_{22}}{{\mathop{\rm x}\nolimits} _2} = {\mathop{\rm c}\nolimits} \) for \({x_2}\).

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Exercises 15 and 16 concern arbitrary matrices A, B, and Cfor which the indicated sums and products are defined. Mark each statement True or False. Justify each answer.

15. a. If A and B are \({\bf{2}} \times {\bf{2}}\) with columns \({{\bf{a}}_1},{{\bf{a}}_2}\) and \({{\bf{b}}_1},{{\bf{b}}_2}\) respectively, then \(AB = \left( {\begin{aligned}{*{20}{c}}{{{\bf{a}}_1}{{\bf{b}}_1}}&{{{\bf{a}}_2}{{\bf{b}}_2}}\end{aligned}} \right)\).

b. Each column of ABis a linear combination of the columns of Busing weights from the corresponding column of A.

c. \(AB + AC = A\left( {B + C} \right)\)

d. \({A^T} + {B^T} = {\left( {A + B} \right)^T}\)

e. The transpose of a product of matrices equals the product of their transposes in the same order.

Exercises 15 and 16 concern arbitrary matrices A, B, and Cfor which the indicated sums and products are defined. Mark each statement True or False. Justify each answer.

16. a. If A and B are \({\bf{3}} \times {\bf{3}}\) and \(B = \left( {\begin{aligned}{*{20}{c}}{{{\bf{b}}_1}}&{{{\bf{b}}_2}}&{{{\bf{b}}_3}}\end{aligned}} \right)\), then \(AB = \left( {A{{\bf{b}}_1} + A{{\bf{b}}_2} + A{{\bf{b}}_3}} \right)\).

b. The second row of ABis the second row of Amultiplied on the right by B.

c. \(\left( {AB} \right)C = \left( {AC} \right)B\)

d. \({\left( {AB} \right)^T} = {A^T}{B^T}\)

e. The transpose of a sum of matrices equals the sum of their transposes.

2. Find the inverse of the matrix \(\left( {\begin{aligned}{*{20}{c}}{\bf{3}}&{\bf{2}}\\{\bf{7}}&{\bf{4}}\end{aligned}} \right)\).

Let \(A = \left( {\begin{aligned}{*{20}{c}}1&1&1\\1&2&3\\1&4&5\end{aligned}} \right)\), and \(D = \left( {\begin{aligned}{*{20}{c}}2&0&0\\0&3&0\\0&0&5\end{aligned}} \right)\). Compute \(AD\) and \(DA\). Explain how the columns or rows of A change when A is multiplied by D on the right or on the left. Find a \(3 \times 3\) matrix B, not the identity matrix or the zero matrix, such that \(AB = BA\).

Show that \({I_n}A = A\) when \(A\) is \(m \times n\) matrix. (Hint: Use the (column) definition of \({I_n}A\).)

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.