Question

Consider the following arrays. 1 4 21 2 4 100 B # 111(A) L3π 42 Write MATLAB expressions to do the tollowing a. Select just the second row of B. b. Evaluate the sum of the second row of B. c. Multiply the second column of B and the first column of A element by element. d. Evaluate the maximum value in the vector resulting from element-by- element multiplication of the second column of B with the first column of A. e. Use element-by-element division to divide the first row of A by the first three elements of the third column of B. Evaluate the sum of the elements of the resulting vector

Answer 1

Answer:

Complete Matalb code along with explanation and output results are given below

Explanation:

We are given following two matrices A and B of size 4x3

A = [1 4 2; 2 4 100; 7 9 7; 3 pi 42]

B = log(A)

(a) Select just the second row of B

% to extract any row use this syntax  B(row no, : )  we can also extract more than 1 row or any particular elements in a specific row

B_row_2 = B(2,:)

(b) Evaluate the sum of the second row of B

% simply use the sum function and pass it any vector or matrix and it will return their sum

sum_B_row_2 = sum( B_row_2(:) )  

(c) Multiply the second column of B and the first column of A element by element

% first we extract the column 2 of matrix B and column 1 of matrix A. use this syntax  B( : ,col no ) to extract any column  

B_col_2 = B(:,2)

A_col_1 = A(:,1)

% Then we use ( .*) to multiply element by element. To use standard multiplication of matrices only use asterisk sign without coma

multiply=B_col_2.*A_col_1

(d) Evaluate the maximum value in the vector resulting from element-by- element multiplication of the second column of B with the first column of A

% we can find the maximum value in a vector or matrix by using max function so we pass the multiply variable where our result was stored

max_value = max(multiply)

(e) Use element-by-element division to divide the first row of A by the first three elements of the third column of B. Evaluate the sum of the elements of the resulting vector

%  First we extract the row 1 of matrix A

A_row_1 = A(1,:)

%  Then we extract the column 3 of matrix B

B_col_3 = B(:,3)

%  Then we extract the first 3 elements of column 3 of matrix B

B_col_3 = B_col_3(1:3)

% Finally we use ( ./ ) to use element by element division

divide = A_row_1./B_col_3

% Using the sum function again results in the addition of entire elements of resultant matrix

sum_divide = sum( divide(:) )

Only Code:

A = [1 4 2; 2 4 100; 7 9 7; 3 pi 42]

B = log(A)

B_row_2 = B(2,:)

sum_B_row_2 = sum( B_row_2(:) )  

B_col_2 = B(:,2)

A_col_1 = A(:,1)

multiply=B_col_2.*A_col_1

max_value = max(multiply)

A_row_1 = A(1,:)

B_col_3 = B(:,3)

B_col_3 = B_col_3(1:3)

divide = A_row_1./B_col_3

sum_divide = sum( divide(:) )

Output Results:

A =

    1.0000     4.0000     2.0000

    2.0000     4.0000   100.0000

    7.0000     9.0000     7.0000

    3.0000     3.1416    42.0000

B =  

  0.00000   1.38629   0.69315

  0.69315   1.38629   4.60517

  1.94591   2.19722   1.94591

  1.09861   1.14473   3.73767

B_row_2 =   0.69315   1.38629   4.60517

sum_B_row_2 =  6.6846

B_col_2 =  

  1.3863

  1.3863

  2.1972

  1.1447

A_col_1 =

  1

  2

  7

  3

multiply =

   1.3863

   2.7726

  15.3806

   3.4342

max_value =  15.381

A_row_1 =     1   4   2

B_col_3 =  

  0.69315

  4.60517

  1.94591

  3.73767

B_col_3 =

  0.69315

  4.60517

  1.94591

divide =

  1.44270   5.77078   2.88539

  0.21715   0.86859   0.43429

  0.51390   2.05559   1.02780

sum_divide =  15.216